Today, mobile devices are widely used by many tourists. They can use mobile for accessing information
about all sightseeing around the world. On the other hand, it seems essential to personalize the content due
to diversity of learners and variation of the tools they use. On the whole, the goal for personalization is to
suggest a collection of comprehensive activities, taking into consideration factors such as location, user
preferences and interests and so on. One of the applications of recommender systems is in tourism industry.
The article covers mobile Applications coverage at Academic Libraries in Pakistan. Hope it will provide some solid and better crux whose are conducting research on the same issues
Designing a recommender system based on social networks and location based se...IJMIT JOURNAL
Mobile devices have diminished spatial limitations, in a way that one can personalize content in a suitable frame considering individual’s location and present it. Yet, it is not possible to consider user’s interests and preferences in a suggestion provided using just place-based services. Current generation of place-based services do not provide users with personalized suggestions, instead they just offer suggestions close to
interests based on users distance from the place where they are. In order to solve this problem, the idea of using social recommender systems was discussed which contains capability of identifying user’s interests and preferences and based on them and user’s current place, it offers some suggestions. Social recommender systems are a combination of social data on web like; user’s social networks and spatial
information. Because user’s information include personal information and interests in social network sites,
considering user’s current location and the information existing in social network data base, it is possible to provide user with a suitable suggestion. Through this method users’ interaction decreases and they can acquire their favorite information and services.
MHEALTH APPLICATIONS DEVELOPED BY THE MINISTRY OF HEALTH FOR PUBLIC USERS INK...hiij
mHealth applications have shown promise in supporting the delivery of health services in peoples’ daily
life. Recently, the Ministry of Health in the Kingdom of Saudi Arabia (MOH) has launched several mHealth
applications to develop work mechanisms. Our study aimed to identify and understand the design of
mHealth apps by classifying their persuasive features using the Persuasive Systems Design (PSD) model
and expert evaluation method. This paper presents the distinct persuasive features applied in recent
applications launched by MOH for public users called “Sehha & Mawid” Apps. The results revealed the
extensive use of persuasive features; particularly features related to credibility support, dialogue support
and primary task support respectively. The implementation and design of social support features were
found to be poor; this could be due to the nature of the apps or lack of knowledge from the developers’
perspectives. The findings suggest some features that may improve the persuasion for the evaluated apps.
The article covers mobile Applications coverage at Academic Libraries in Pakistan. Hope it will provide some solid and better crux whose are conducting research on the same issues
Designing a recommender system based on social networks and location based se...IJMIT JOURNAL
Mobile devices have diminished spatial limitations, in a way that one can personalize content in a suitable frame considering individual’s location and present it. Yet, it is not possible to consider user’s interests and preferences in a suggestion provided using just place-based services. Current generation of place-based services do not provide users with personalized suggestions, instead they just offer suggestions close to
interests based on users distance from the place where they are. In order to solve this problem, the idea of using social recommender systems was discussed which contains capability of identifying user’s interests and preferences and based on them and user’s current place, it offers some suggestions. Social recommender systems are a combination of social data on web like; user’s social networks and spatial
information. Because user’s information include personal information and interests in social network sites,
considering user’s current location and the information existing in social network data base, it is possible to provide user with a suitable suggestion. Through this method users’ interaction decreases and they can acquire their favorite information and services.
MHEALTH APPLICATIONS DEVELOPED BY THE MINISTRY OF HEALTH FOR PUBLIC USERS INK...hiij
mHealth applications have shown promise in supporting the delivery of health services in peoples’ daily
life. Recently, the Ministry of Health in the Kingdom of Saudi Arabia (MOH) has launched several mHealth
applications to develop work mechanisms. Our study aimed to identify and understand the design of
mHealth apps by classifying their persuasive features using the Persuasive Systems Design (PSD) model
and expert evaluation method. This paper presents the distinct persuasive features applied in recent
applications launched by MOH for public users called “Sehha & Mawid” Apps. The results revealed the
extensive use of persuasive features; particularly features related to credibility support, dialogue support
and primary task support respectively. The implementation and design of social support features were
found to be poor; this could be due to the nature of the apps or lack of knowledge from the developers’
perspectives. The findings suggest some features that may improve the persuasion for the evaluated apps.
The real challenge in the modern world is not producing information or storing information,
but apt and proper use of information by people. Since volume of information is growing in leaps
and bounds, the information needs of users are becoming more and more diverse and complex. In
this changing context information providers are facing a lot of challenges to capture, process, store
and disseminate the available information for actual users. The user studies provide a clear
understanding of the actual information needs of the user in order to readjust the existing
information systems or chose new ones. Various models of information needs and informationseeking behaviour have been discussed. Each modelrepresents a different but an overlapping or
similar approach to information seeking behavior of users. In order to satisfy the information need,the user actively undergoes the information seeking processes. Some factors like physiological,emotional, learning and demographic, etc. also deeply influence information seeking behaviour i.e.
some people have to face some obstacles. These barriers may be economic, social, environmental,
time related or geographical.Effectiveness of a professional depends upon dissemination and use of right information at
right time. Information and communication technologies have changed the way in which thelibraries provide their services. Users study provide deeperunderstanding of access to their
collections and services .The need and behavior of their users and satisfaction ratio of users are
new assessment techniques of libraries. Therefore an effort has been made to how determineinformation need and information seeking behavior of users.
SMART AGENT BASED SEARCH FOR ADMISSION IN INSTITUTIONS OF HIGHER LEARNINGIJITE
Early admission systems saw people applying to universities by filling out applications forms and placing
them in suitable envelopes and sending them through the local postal agency. This was not considered to
be cost or time effective, and this method was also not efficient. This system however needed some
improvement due to the huge workload on administrators. So researchers and software developers
improved the system so that between 1999 and 2008 application and admission was done via the Internet.
Also many Ranking system like ARWU, shanghai etc. been used for ranking the universities and colleges
around the world which would enable people choosing the universities and colleges for education on
factors like publication, funding, infrastructure and so.
The Internet has already brought the humans together in a new, exciting, and unexpected ways, and the
same is also happening to our prevalent adoption of digital mobile devices that has paved the way for the
development of many innovative applications in the commercial domain. While considering such mobile
devices for an application towards higher education in an educational institution, there has been some
amount of work done using intelligent agents. But still those agent based systems got some drawbacks
which motivated towards developing the present Agent based system to provide Smart agent based system
for higher Learning search not in Jamaican context alone but also elsewhere with these drawbacks
alleviated. The agents developed will be based on using fuzzy preference rules and heuristics, to make
accurate decisions based on the user’s criteria or specifications using JADE-LEAP on Android handset.
The system got Google map feature, intelligence in admission system and also warning for universities
with low rating. These findings of this research will be presented as screenshots.
Classifying web users in a personalised search setup is cumbersome due the very nature of dynamism in
user browsing history. This fluctuating nature of user behaviour and user interest shall be well interpreted
within a fuzzy setting. Prior to analysing user behaviour, nature of user interests has to be collected. This
work proposes a fuzzy based user classification model to suit a personalised web search environment. The
user browsing data is collected using an established customised browser designed to suit personalisation.
The data are fuzzified and fuzzy rules are generated by applying decision trees. Using fuzzy rules, the
search pages are labelled to aid grouping of user search interests. Evaluation of the proposed approach
proves to be better when compared with Bayesian classifier.
A survey on a cocktail approach for travel package recommendationeSAT Journals
Abstract Providing better travel services for tourists is one of the important applications in urban computing. The worlds is of commerce, travel, entertainment, and Internet technology are linked, different types of business data is accessible for innovative use and regular analysis. Here it provides a study of utilizing online travel information for the personalized travel package recommendation. Though many recommender systems have been developed for enhancing the quality of travel service, most of them lack a systematic and open framework to dynamically incorporate multiple types of additional context information existing in the tourism domain, such as the travel area, season, and price of the travel packages. First analyze the properties of the old travel packages and develop a tourist-area-season topic (TAST) model. This TAST model represents different travel packages and different topic distributions of tourist, the topic extraction is stated on both the tourists and the natural characteristics of the landscapes. According to the topic model representation, a cocktail approach is generated so that to form lists for personalized travel package recommendation. The TAST model is extended to the tourist-relation-area-season topic (TRAST) model for collecting the relationships among the tourists for all travel groups. Then analyze TAST model, TRAST model, and cocktail recommendation approach on the current travel package data. The TAST model can effectively grabs the individual characteristics of travel data and cocktail approach, so it is more efficient than old recommendation techniques for travel package recommendation by including tourist relationships, TRAST model is used as an effective evaluation for travel group formation. Keywords: Travel package, recommender systems, cocktail, topic modeling, collaborative filtering
Research often spend a considerable amount of time searching for published papers and articles relevant to their interest, dissertation and research work. A recommender engine is a tool, a means to answer the question. “What are the best recommendations for a user?” Using trust in social networks provides a promising approach to make recommendations to other user based on trust propagation in finding research papers or research papers of a friend/research with similar interests. However, current recommendation algorithms are based on user-item rating. A collaborative filtering based research paper recommender system is proposed here with User and Item Based collaborative filtering approach to implement a recommender system for Research Paper.
DESIGNING A RECOMMENDER SYSTEM BASED ON SOCIAL NETWORKS AND LOCATION BASED ...IJMIT JOURNAL
Mobile devices have diminished spatial limitations, in a way that one can personalize content in a suitable
frame considering individual’s location and present it. Yet, it is not possible to consider user’s interests and
preferences in a suggestion provided using just place-based services. Current generation of place-based
services do not provide users with personalized suggestions, instead they just offer suggestions close to
interests based on users distance from the place where they are. In order to solve this problem, the idea of
using social recommender systems was discussed which contains capability of identifying user’s interests
and preferences and based on them and user’s current place, it offers some suggestions. Social
recommender systems are a combination of social data on web like; user’s social networks and spatial
information. Because user’s information include personal information and interests in social network sites,
considering user’s current location and the information existing in social network data base, it is possible
to provide user with a suitable suggestion. Through this method users’ interaction decreases and they can
acquire their favorite information and services.
Basically the project is having two parts namely the recommender system and the planner system. The tour
recommender system firstly asks the user for logging in then he asks for the various details about his tour in order
to recommend a perfect tour. The recommender system collects the information regarding the type of place, the
travelling method the user would like to prefer and more importantly the cost which the user can afford. The
collected data is sent to the recommender algorithm which processes the data and finds a perfect place with
required specification from the system database. Three best results are displayed. Then the user selects one tour as
per his choice. Next the planner system displays all the possible travelling and accommodation methods with their
costs and offers. Then the user selects the services according to his convenience and enjoys the trip.
A location based movie recommender systemijfcstjournal
Available recommender systems mostly provide recommendations based on the users’ preferences by
utilizing traditional methods such as collaborative filtering which only relies on the similarities between users and items. However, collaborative filtering might lead to provide poor recommendation because it does not rely on other useful available data such as users’ locations and hence the accuracy of the recommendations could be very low and inefficient. This could be very obvious in the systems that locations would affect users’ preferences highly such as movie recommender systems. In this paper a new locationbased movie recommender system based on the collaborative filtering is introduced for enhancing the
accuracy and the quality of recommendations. In this approach, users’ locations have been utilized and
take in consideration in the entire processing of the recommendations and peer selections. The potential of
the proposed approach in providing novel and better quality recommendations have been discussed through experiments in real datasets.
A LOCATION-BASED MOVIE RECOMMENDER SYSTEM USING COLLABORATIVE FILTERINGijfcstjournal
Available recommender systems mostly provide recommendations based on the users’ preferences by
utilizing traditional methods such as collaborative filtering which only relies on the similarities between
users and items. However, collaborative filtering might lead to provide poor recommendation because it
does not rely on other useful available data such as users’ locations and hence the accuracy of the
recommendations could be very low and inefficient. This could be very obvious in the systems that locations
would affect users’ preferences highly such as movie recommender systems. In this paper a new locationbased movie recommender system based on the collaborative filtering is introduced for enhancing the
accuracy and the quality of recommendations. In this approach, users’ locations have been utilized and
take in consideration in the entire processing of the recommendations and peer selections. The potential of
the proposed approach in providing novel and better quality recommendations have been discussed
through experiments in real datasets.
Machine learning based recommender system for e-commerceIAESIJAI
Nowadays, e-commerce is becoming an essential part of business for many reasons, including the simplicity, availability, richness and diversity of products and services, flexibility of payment methods and the convenience of shopping remotely without losing time. These benefits have greatly optimized the lives of users, especially with the technological development of mobile devices and the availability of the Internet anytime and anywhere. Because of their direct impact on the revenue of e-commerce companies, recommender systems are considered a must in this field. Recommender systems detect items that match the customer's needs based on the customer's previous actions and make them appear in an interesting way. Such a customized experience helps to increase customer engagement and purchase rates as the suggested items are tailored to the customer's interests. Therefore, perfecting recommendation systems that allow for more personalized and accurate item recommendations is a major challenge in the e-marketing world. In our study, we succeeded in developing an algorithm to suggest personal recommendations to customers using association rules via the Frequent-Pattern-Growth algorithm. Our technique generated good results with a high average probability of purchasing the next product suggested by the recommendation system.
Personalized E-commerce based recommendation systems using deep-learning tech...IAESIJAI
As technology is surpassing each day, with the variation of personalized drifts
relevant to the explicit behavior of users using the internet. Recommendation
systems use predictive mechanisms like predicting a rating that a customer
could give on a specific item. This establishes a ranked list of items according
to the preferences each user makes concerning exhibiting personalized
recommendations. The existing recommendation techniques are efficient in
systematically creating recommendation techniques. This approach
encounters many challenges such as determining the accuracy, scalability, and
data sparsity. Recently deep learning attains significant research to enhance
the performance to improvise feature specification in learning the efficiency
of retrieving the necessary information as well as a recommendation system
approach. Here, we provide a thorough review of the deep-learning
mechanism focused on the learning-rates-based prediction approach modeled
to articulate the widespread summary for the state-of-art techniques. The
novel techniques ensure the incorporation of innovative perspectives to
pertain to the unique and exciting growth in this field.
A Hypothesis is Placed to Justify the Extendibility of Recommender System/ Re...Dr. Amarjeet Singh
Researchers still believe that the information filtering system/ collaborating system is a recommender system or a recommendation system. It is used to predict the "rating" or "preference" of a user to an item. In other words, both predict rating or preference for an item or product on a specific platform. The aim of the paper is to extend the areas of the recommender system/recommendation systems. The basic task of the recommender system mainly is to predict or analyze items/product. If it is possible to include more products in the system, then obviously the system may be extended for other areas also. For example, Medicine is a product and doctors filter the particular medicine for the particular disease. In the medical diagnosis doctors prescribed a medicine and it a product. It depends on the disease of the user/patient so here doctor predicts a medicine or product just like an item is recommended in a recommender system. The main objective of the paper is to extend the Recommender System/Recommendation system in other fields so that the research works can be extended Social Science, Bio-medical Science and many other areas.
Happy Hours is a time-limited offer strategy which attracts people by providing maximum
discounts. People are not aware about these offers going in their nearby areas because of their busy
schedule. Mobile device is ubiquity available with customers everywhere and all the time which can help
in personalizing advertisements with the help of spatial information and various other parameters.
Existing systems use SMS to notify users about advertisements and SMS has limitations. Traditional
systems use request-response pattern where user needs to always submit query which ultimately
degrades user experience. Also mobile visualization ends up with too much too visualize in a too little
display area. Our proposed system considers all of the above issues and leverages the strengths of
proactive model and context-aware personalized dashboard for Happy Hours and their Deals
recommendations.
The real challenge in the modern world is not producing information or storing information,
but apt and proper use of information by people. Since volume of information is growing in leaps
and bounds, the information needs of users are becoming more and more diverse and complex. In
this changing context information providers are facing a lot of challenges to capture, process, store
and disseminate the available information for actual users. The user studies provide a clear
understanding of the actual information needs of the user in order to readjust the existing
information systems or chose new ones. Various models of information needs and informationseeking behaviour have been discussed. Each modelrepresents a different but an overlapping or
similar approach to information seeking behavior of users. In order to satisfy the information need,the user actively undergoes the information seeking processes. Some factors like physiological,emotional, learning and demographic, etc. also deeply influence information seeking behaviour i.e.
some people have to face some obstacles. These barriers may be economic, social, environmental,
time related or geographical.Effectiveness of a professional depends upon dissemination and use of right information at
right time. Information and communication technologies have changed the way in which thelibraries provide their services. Users study provide deeperunderstanding of access to their
collections and services .The need and behavior of their users and satisfaction ratio of users are
new assessment techniques of libraries. Therefore an effort has been made to how determineinformation need and information seeking behavior of users.
SMART AGENT BASED SEARCH FOR ADMISSION IN INSTITUTIONS OF HIGHER LEARNINGIJITE
Early admission systems saw people applying to universities by filling out applications forms and placing
them in suitable envelopes and sending them through the local postal agency. This was not considered to
be cost or time effective, and this method was also not efficient. This system however needed some
improvement due to the huge workload on administrators. So researchers and software developers
improved the system so that between 1999 and 2008 application and admission was done via the Internet.
Also many Ranking system like ARWU, shanghai etc. been used for ranking the universities and colleges
around the world which would enable people choosing the universities and colleges for education on
factors like publication, funding, infrastructure and so.
The Internet has already brought the humans together in a new, exciting, and unexpected ways, and the
same is also happening to our prevalent adoption of digital mobile devices that has paved the way for the
development of many innovative applications in the commercial domain. While considering such mobile
devices for an application towards higher education in an educational institution, there has been some
amount of work done using intelligent agents. But still those agent based systems got some drawbacks
which motivated towards developing the present Agent based system to provide Smart agent based system
for higher Learning search not in Jamaican context alone but also elsewhere with these drawbacks
alleviated. The agents developed will be based on using fuzzy preference rules and heuristics, to make
accurate decisions based on the user’s criteria or specifications using JADE-LEAP on Android handset.
The system got Google map feature, intelligence in admission system and also warning for universities
with low rating. These findings of this research will be presented as screenshots.
Classifying web users in a personalised search setup is cumbersome due the very nature of dynamism in
user browsing history. This fluctuating nature of user behaviour and user interest shall be well interpreted
within a fuzzy setting. Prior to analysing user behaviour, nature of user interests has to be collected. This
work proposes a fuzzy based user classification model to suit a personalised web search environment. The
user browsing data is collected using an established customised browser designed to suit personalisation.
The data are fuzzified and fuzzy rules are generated by applying decision trees. Using fuzzy rules, the
search pages are labelled to aid grouping of user search interests. Evaluation of the proposed approach
proves to be better when compared with Bayesian classifier.
A survey on a cocktail approach for travel package recommendationeSAT Journals
Abstract Providing better travel services for tourists is one of the important applications in urban computing. The worlds is of commerce, travel, entertainment, and Internet technology are linked, different types of business data is accessible for innovative use and regular analysis. Here it provides a study of utilizing online travel information for the personalized travel package recommendation. Though many recommender systems have been developed for enhancing the quality of travel service, most of them lack a systematic and open framework to dynamically incorporate multiple types of additional context information existing in the tourism domain, such as the travel area, season, and price of the travel packages. First analyze the properties of the old travel packages and develop a tourist-area-season topic (TAST) model. This TAST model represents different travel packages and different topic distributions of tourist, the topic extraction is stated on both the tourists and the natural characteristics of the landscapes. According to the topic model representation, a cocktail approach is generated so that to form lists for personalized travel package recommendation. The TAST model is extended to the tourist-relation-area-season topic (TRAST) model for collecting the relationships among the tourists for all travel groups. Then analyze TAST model, TRAST model, and cocktail recommendation approach on the current travel package data. The TAST model can effectively grabs the individual characteristics of travel data and cocktail approach, so it is more efficient than old recommendation techniques for travel package recommendation by including tourist relationships, TRAST model is used as an effective evaluation for travel group formation. Keywords: Travel package, recommender systems, cocktail, topic modeling, collaborative filtering
Research often spend a considerable amount of time searching for published papers and articles relevant to their interest, dissertation and research work. A recommender engine is a tool, a means to answer the question. “What are the best recommendations for a user?” Using trust in social networks provides a promising approach to make recommendations to other user based on trust propagation in finding research papers or research papers of a friend/research with similar interests. However, current recommendation algorithms are based on user-item rating. A collaborative filtering based research paper recommender system is proposed here with User and Item Based collaborative filtering approach to implement a recommender system for Research Paper.
DESIGNING A RECOMMENDER SYSTEM BASED ON SOCIAL NETWORKS AND LOCATION BASED ...IJMIT JOURNAL
Mobile devices have diminished spatial limitations, in a way that one can personalize content in a suitable
frame considering individual’s location and present it. Yet, it is not possible to consider user’s interests and
preferences in a suggestion provided using just place-based services. Current generation of place-based
services do not provide users with personalized suggestions, instead they just offer suggestions close to
interests based on users distance from the place where they are. In order to solve this problem, the idea of
using social recommender systems was discussed which contains capability of identifying user’s interests
and preferences and based on them and user’s current place, it offers some suggestions. Social
recommender systems are a combination of social data on web like; user’s social networks and spatial
information. Because user’s information include personal information and interests in social network sites,
considering user’s current location and the information existing in social network data base, it is possible
to provide user with a suitable suggestion. Through this method users’ interaction decreases and they can
acquire their favorite information and services.
Basically the project is having two parts namely the recommender system and the planner system. The tour
recommender system firstly asks the user for logging in then he asks for the various details about his tour in order
to recommend a perfect tour. The recommender system collects the information regarding the type of place, the
travelling method the user would like to prefer and more importantly the cost which the user can afford. The
collected data is sent to the recommender algorithm which processes the data and finds a perfect place with
required specification from the system database. Three best results are displayed. Then the user selects one tour as
per his choice. Next the planner system displays all the possible travelling and accommodation methods with their
costs and offers. Then the user selects the services according to his convenience and enjoys the trip.
A location based movie recommender systemijfcstjournal
Available recommender systems mostly provide recommendations based on the users’ preferences by
utilizing traditional methods such as collaborative filtering which only relies on the similarities between users and items. However, collaborative filtering might lead to provide poor recommendation because it does not rely on other useful available data such as users’ locations and hence the accuracy of the recommendations could be very low and inefficient. This could be very obvious in the systems that locations would affect users’ preferences highly such as movie recommender systems. In this paper a new locationbased movie recommender system based on the collaborative filtering is introduced for enhancing the
accuracy and the quality of recommendations. In this approach, users’ locations have been utilized and
take in consideration in the entire processing of the recommendations and peer selections. The potential of
the proposed approach in providing novel and better quality recommendations have been discussed through experiments in real datasets.
A LOCATION-BASED MOVIE RECOMMENDER SYSTEM USING COLLABORATIVE FILTERINGijfcstjournal
Available recommender systems mostly provide recommendations based on the users’ preferences by
utilizing traditional methods such as collaborative filtering which only relies on the similarities between
users and items. However, collaborative filtering might lead to provide poor recommendation because it
does not rely on other useful available data such as users’ locations and hence the accuracy of the
recommendations could be very low and inefficient. This could be very obvious in the systems that locations
would affect users’ preferences highly such as movie recommender systems. In this paper a new locationbased movie recommender system based on the collaborative filtering is introduced for enhancing the
accuracy and the quality of recommendations. In this approach, users’ locations have been utilized and
take in consideration in the entire processing of the recommendations and peer selections. The potential of
the proposed approach in providing novel and better quality recommendations have been discussed
through experiments in real datasets.
Machine learning based recommender system for e-commerceIAESIJAI
Nowadays, e-commerce is becoming an essential part of business for many reasons, including the simplicity, availability, richness and diversity of products and services, flexibility of payment methods and the convenience of shopping remotely without losing time. These benefits have greatly optimized the lives of users, especially with the technological development of mobile devices and the availability of the Internet anytime and anywhere. Because of their direct impact on the revenue of e-commerce companies, recommender systems are considered a must in this field. Recommender systems detect items that match the customer's needs based on the customer's previous actions and make them appear in an interesting way. Such a customized experience helps to increase customer engagement and purchase rates as the suggested items are tailored to the customer's interests. Therefore, perfecting recommendation systems that allow for more personalized and accurate item recommendations is a major challenge in the e-marketing world. In our study, we succeeded in developing an algorithm to suggest personal recommendations to customers using association rules via the Frequent-Pattern-Growth algorithm. Our technique generated good results with a high average probability of purchasing the next product suggested by the recommendation system.
Personalized E-commerce based recommendation systems using deep-learning tech...IAESIJAI
As technology is surpassing each day, with the variation of personalized drifts
relevant to the explicit behavior of users using the internet. Recommendation
systems use predictive mechanisms like predicting a rating that a customer
could give on a specific item. This establishes a ranked list of items according
to the preferences each user makes concerning exhibiting personalized
recommendations. The existing recommendation techniques are efficient in
systematically creating recommendation techniques. This approach
encounters many challenges such as determining the accuracy, scalability, and
data sparsity. Recently deep learning attains significant research to enhance
the performance to improvise feature specification in learning the efficiency
of retrieving the necessary information as well as a recommendation system
approach. Here, we provide a thorough review of the deep-learning
mechanism focused on the learning-rates-based prediction approach modeled
to articulate the widespread summary for the state-of-art techniques. The
novel techniques ensure the incorporation of innovative perspectives to
pertain to the unique and exciting growth in this field.
A Hypothesis is Placed to Justify the Extendibility of Recommender System/ Re...Dr. Amarjeet Singh
Researchers still believe that the information filtering system/ collaborating system is a recommender system or a recommendation system. It is used to predict the "rating" or "preference" of a user to an item. In other words, both predict rating or preference for an item or product on a specific platform. The aim of the paper is to extend the areas of the recommender system/recommendation systems. The basic task of the recommender system mainly is to predict or analyze items/product. If it is possible to include more products in the system, then obviously the system may be extended for other areas also. For example, Medicine is a product and doctors filter the particular medicine for the particular disease. In the medical diagnosis doctors prescribed a medicine and it a product. It depends on the disease of the user/patient so here doctor predicts a medicine or product just like an item is recommended in a recommender system. The main objective of the paper is to extend the Recommender System/Recommendation system in other fields so that the research works can be extended Social Science, Bio-medical Science and many other areas.
Happy Hours is a time-limited offer strategy which attracts people by providing maximum
discounts. People are not aware about these offers going in their nearby areas because of their busy
schedule. Mobile device is ubiquity available with customers everywhere and all the time which can help
in personalizing advertisements with the help of spatial information and various other parameters.
Existing systems use SMS to notify users about advertisements and SMS has limitations. Traditional
systems use request-response pattern where user needs to always submit query which ultimately
degrades user experience. Also mobile visualization ends up with too much too visualize in a too little
display area. Our proposed system considers all of the above issues and leverages the strengths of
proactive model and context-aware personalized dashboard for Happy Hours and their Deals
recommendations.
Review and analysis of machine learning and soft computing approaches for use...IJwest
The adequacy of user models depends mainly on the accuracy and precision of information that is retrieved to the user. The real challenge in user modelling studies is due to the inadequacy of data, improper use of techniques, noise within the data and imprecise nature of human behavior. For the best results of user modelling, one should choose an appropriate way to do it i.e. by selecting the best suitable approach for the desired domain. Machine learning and Soft computing Techniques have the ability to handle the uncertainty and are extensively being used for user modeling purpose. This paper reviews various approaches of user modeling and critically analyzes the machine learning and soft computing techniques that have successfully captured and formally modelled the human behavior.
Web search engines help users find useful information on the WWW. However, when the same
query is submitted by different users, typical search engines return the same result regardless of who
submitted the query. Generally, each user has different information needs for his/her query. Therefore,
the search results should be adapted to users with different information needs. So, there is need of
several approaches to adapting search results according to each user’s need for relevant information
without any user effort. Such search systems that adapt to each user’s preferences can be achieved by
constructing user profiles based on modified collaborative filtering with detailed analysis of user’s
browsing history.
There are three possible types of web search system which can provide personalized
information: (1) systems using relevance feedback, (2) systems in which users register their interest, and
(3) systems that recommend information based on user’s history. In first technique, users have to provide
feedback on relevant or irrelevant judgments which is time consuming and the second one needs
registration of users with their static interests which need extra effort from user. So, the third technique
is best in which users don’t have to give explicit rating; relevancy automatically tracked by user
behavior with search results and history of data usage. It doesn’t require registration of interests; it
captures changing interests of user dynamically by itself. The result section shows that user’s browsing
history allows each user to perform more fine-grained search by capturing changes of each user’s
preferences without any user effort. Users need less time to find the relevant snippet in personalized
search results compared to original results
In artificial intelligence, an expert system is the computer system that emulates the decision making ability of a human expert. Expert systems are designed to solve the complex problems by reasoning about the knowledge represented primarily as If-then rules rather than through conventional procedural code Intelligent Travelling System is the system that will run on most of the phones and palms which enable the user to visit the places at user criteria . In the current situations, systems have the information about the places they want to visit and they don’t have usable or valuable information about points of interest except the phone numbers and addresses. In order to overcome this problem the Intelligent Travelling System has been proposed. The users who want to travel around can answer the set of questions and the system will provide tourist spot, path to the spot, some picture of the spot and rough estimated cost based on the answers given by the user. The primary advantage of this system is to fulfill user criteria by approximate estimation of cost and time.
MULTIMODAL COURSE DESIGN AND IMPLEMENTATION USING LEML AND LMS FOR INSTRUCTIO...IJMIT JOURNAL
Traditionally, teaching has been centered around classroom delivery. However, the onslaught of the
COVID-19 pandemic has cultivated usage of technology, teaching, and learning methodologies for course
delivery. We investigate and describe different modes of course delivery that maintain the integrity of
teaching and learning. This paper answers to the research questions: 1) What course delivery method our
academic institutions use and why? 2) How can instructors validate the guidelines of the institutions? 3)
How courses should be taught to provide student learning outcomes? Using the Learning Environment
Modeling Language (LEML), we investigate the design and implementation of courses for delivery in the
following environments: face-to-face, online synchronous, asynchronous, hybrid, and hyflex. A good
course design and implementation are key components of instructional alignment. Furthermore, we
demonstrate how to design, implement, and deliver courses in synchronous, asynchronous, and hybrid
modes and describe our proposed enhancements to LEML.
Novel R&D Capabilities as a Response to ESG Risks-Lessons From Amazon’s Fusio...IJMIT JOURNAL
Environmental, Social, and Governance (ESG) management is essential for transforming corporate
financial performance-oriented business strategies into Finance (F) + ESG optimization strategies to
achieve the Sustainable Development Goals (SDGs).
In this trend, the rise of ESG risks has divided firms into two categories. Former incorporates a growthmindset that creates a passion for learning, and urges it to improve itself by endeavoring Research and
development (R&D) -driven challenges, while the other category, characterized by risk aversion, avoids
challenging highly uncertain R&D activities and seeks more manageable endeavors.
This duality underscores the complexity of corporate R&D strategies in addressing ESG risks and
necessitates the development of novel R&D capabilities for corporate R&D transformation strategies
towards F + ESG optimization.
International Journal of Managing Information Technology (IJMIT) ** WJCI IndexedIJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental. The goal of this journal is to bring together researchers and practitioners from academia, government, and industry to focus on understanding both how to use IT to support the strategy and goals of the organization and to employ IT in new ways to foster greater collaboration, communication, and information sharing both within the organization and with its stakeholders. The International Journal of Managing Information Technology seeks to establish new collaborations, new best practices, and new theories in these areas.
International Journal of Managing Information Technology (IJMIT) ** WJCI IndexedIJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental. The goal of this journal is to bring together researchers and practitioners from academia, government, and industry to focus on understanding both how to use IT to support the strategy and goals of the organization and to employ IT in new ways to foster greater collaboration, communication, and information sharing both within the organization and with its stakeholders. The International Journal of Managing Information Technology seeks to establish new collaborations, new best practices, and new theories in these areas.
NOVEL R & D CAPABILITIES AS A RESPONSE TO ESG RISKS- LESSONS FROM AMAZON’S FU...IJMIT JOURNAL
Environmental, Social, and Governance (ESG) management is essential for transforming corporate
financial performance-oriented business strategies into Finance (F) + ESG optimization strategies to
achieve the Sustainable Development Goals (SDGs).
In this trend, the rise of ESG risks has divided firms into two categories. Former incorporates a growthmindset that creates a passion for learning, and urges it to improve itself by endeavoring Research and
development (R&D) -driven challenges, while the other category, characterized by risk aversion, avoids
challenging highly uncertain R&D activities and seeks more manageable endeavors.
This duality underscores the complexity of corporate R&D strategies in addressing ESG risks and
necessitates the development of novel R&D capabilities for corporate R&D transformation strategies
towards F + ESG optimization.
Building on this premise, this paper conducts an empirical analysis, utilizing reliable firms data on ESG
risk and brand value, with a focus on 100 global R&D leader firms. It analyzes R&D and actions for ESG
risk mitigation, and assesses the development of new functions that fulfill F + ESG optimization through
R&D. The analysis also highlights the significance of network externality effects, with a specific focus on
Amazon, a leading R&D company, providing insights into the direction for transforming R&D strategies
towards F + ESG optimization.
The dynamics of stakeholder engagement in F + ESG optimization are indicated with the example of
amazon's activities. Through the analysis, it became evident that Amazon's capacity encompassing growth
and scalability, specifically its ability to grow and expand, is accelerating high-level research and
development by gaining the trust of stakeholders in the "synergy through R&D-driven ESG risk
mitigation."
Finally, as examples of these initiatives, the paper discussed the Climate Pledge led by Amazon and the
transformation of Japan's management system.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both
these capabilities are very important for an investor in order to obtain maximized profit and minimized
losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends
and market conditions. Technical analysis helps to understand stock prices behavior with regards to past
trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase
investment performance by taking into account the global performance and the proposed combination of
effective multi technical indicator strategy model.
INTRUSION DETECTION SYSTEM USING CUSTOMIZED RULES FOR SNORTIJMIT JOURNAL
These days the security provided by the computer systems is a big issue as it always has the threats of
cyber-attacks like IP address spoofing, Denial of Service (DOS), token impersonation, etc. The security
provided by the blue team operations tends to be costly if done in large firms as a large number of systems
need to be protected against these attacks. This leads these firms to turn to less costly security
configurations like IDS Suricata and IDS Snort. The main theme of the project is to improve the services
provided by Snort which is a tool used in creating a vague defense against cyber-attacks like DDOS
attacks which are done on both physical and network layers. These attacks in turn result in loss of
extremely important data. The rules defined in this project will result in monitoring traffic, analyzing it,
and taking appropriate action to not only stop the attack but also locate its source IP address. This whole
process uses different tools other than Snort like Wireshark, Wazuh and Splunk. The product of this will
result in not only the detection of the attack but also the source IP address of the machine on which the
attack is initiated and completed. The end product of this research will result in sets of default rules for the
Snort tool which will not only be able to provide better security than its previous versions but also be able
to provide the user with the IP address of the attacker or the person conducting the attack. The system
involves the integration of Wazuh with Snort tool in order to make it more efficient than IDS Suricata
which is another intrusion detection system capable of detecting all these types of attacks as mentioned.
Splunk is another tool used in this project which increases the firewall efficiency to pass the no. of bits to
be scanned and the no. of bits scanned successfully. Wazuh is used in this system as it is the best choice for
traffic monitoring and incident response than any other of its alternatives in the market. Since this system
is used in firms which are known to handle big amounts of data and for this purpose, we use Splunk tool as
it is very efficient in handling big amounts of data. Wireshark is used in this system in order to give the IDS
automation in its capability to capture and report the malicious packets found during the network scan. All
of this gives the IDS a capability of a low budget automated threat detection system. This paper gives
complete guidelines for authors submitting papers for the AIRCC Journals.
Artificial Intelligence (AI) has rapidly become a critical technology for businesses seeking to improve
efficiency and profitability. One area where AI is proving particularly impactful is in service operations
management, where it is used to create AI-powered service operations (AIServiceOps) that deliver highvalue services to customers. AIServiceOps involve the use of AI to automate and optimize various business
processes, such as customer service, sales, marketing, and supply chain management. The rapid
development of Artificial Intelligence has prompted many changes in the field of Information Technology
(IT) Service Operations. IT Service Operations are driven by AI, i.e., AIServiceOps. AI has empowered
new vitality and addressed many challenges in IT Service Operations. However, there is a literature gap on
the Business Value Impact of Artificial intelligence (AI) Powered IT Service Operations. It can help IT
build optimized business resilience by creating value in complex and ever-changing environments as
product organizations move faster than IT can handle. So, this research paper examines how AIServiceOps
creates business value and sustainability, basically how AIServiceOps makes the IT staff liberation from a
low-level, repetitive workout and traditional IT practices for a continuously optimized process. One of the
research objectives is to compare Traditional IT Service Operations with AIServiceOPs. This paper
provides the basis for how enterprises can evaluate AIServiceOps and consider it a digital transformation
tool. The paper presents a case study of a company that implemented AI-powered service operations
(AIServiceOps) and analyzes the resulting business outcomes. The study shows that AIServiceOps can
significantly improve service delivery, reduce response times, and increase customer satisfaction.
Furthermore, it demonstrates how AIServiceOps can deliver substantial cost savings, such as reducing
labor costs and minimizing downtime.
MEDIATING AND MODERATING FACTORS AFFECTING READINESS TO IOT APPLICATIONS: THE...IJMIT JOURNAL
Although IOT seems to be the upcoming trend, it is still in its infancy; especially in the banking industry.
There is a clear gap in literature, as only few studies identify factors affecting readiness to IOT
applications in banks in general, and almost negligible investigations on mediating and moderating
factors. Accordingly, this research aims to investigate the main factors that affect employees’ readiness to
IOT applications, while highlighting the mediating and moderating factors in the Egyptian banking sector.
The importance of Egypt stems from its high population and steady steps taken towards technology
adoption. 479 valid questionnaires were distributed over HR employees in banks. Data collected was
statistically analysed using Regression and SEM. Results showed a significant impact of ‘Security’,
‘Networking’, ‘Software Development’ and ‘Regulations’ on ‘readiness to IOT applications. Thus, the
readiness acceptance level is high‘Security’ and ‘User Intention’ were proven to mediate the relationship
between research variables and readiness to IOT applications, and only a partial moderation role was
proven for ‘Efficiency’. The study contributes to increasing literature on IOT applications in general, and
fills a gap on the Egyptian banking context in particular. Finally, it provides decision makers at banks with
useful guidelines on how to optimally promote IOT applications among employees.
EFFECTIVELY CONNECT ACQUIRED TECHNOLOGY TO INNOVATION OVER A LONG PERIODIJMIT JOURNAL
IT (Information and Communication Technology) companies are facing the dilemma of decreasing
productivity despite increasing research and development efforts. M&A (Merger and Acquisition) is being
considered as a breakthrough solution. From existing research, it has been pointed out that M&A leads to
the emergence of new innovations. Purpose of this study was to discuss the efficient ways of acquisition and
to resolve the dilemma of productivity decline by clarifying how the technology obtained through M&A
leads to the creation of new innovations. Hypothesis 1 was that the technology acquired through M&A is
utilized for innovation creation, Hypothesis 2 was that the acquired technology is utilized over a long
period of time, and Hypothesis 3 was that a long-term utilization has a positive impact on corporate
performance. The results, using sports prosthetics as a case study and using patents as a proxy variable,
confirmed all the hypotheses set. We have revealed that long-term utilization of technology obtained
through M&A is effective for creating new innovations.
International Journal of Managing Information Technology (IJMIT) ** WJCI IndexedIJMIT JOURNAL
The International Journal of Managing Information Technology (IJMIT) is a quarterly open access peer-reviewed journal that publishes articles that contribute new results in all areas of the strategic application of information technology (IT) in organizations. The journal focuses on innovative ideas and best practices in using IT to advance organizations – for-profit, non-profit, and governmental. The goal of this journal is to bring together researchers and practitioners from academia, government, and industry to focus on understanding both how to use IT to support the strategy and goals of the organization and to employ IT in new ways to foster greater collaboration, communication, and information sharing both within the organization and with its stakeholders. The International Journal of Managing Information Technology seeks to establish new collaborations, new best practices, and new theories in these areas.
Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the areas of information technology and management
4th International Conference on Cloud, Big Data and IoT (CBIoT 2023)IJMIT JOURNAL
4th International Conference on Cloud, Big Data and IoT (CBIoT 2023) will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the areas of Cloud, Big Data and IoT. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of Cloud, Big Data and IoT.
Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Cloud, Big Data and IoT.
TRANSFORMING SERVICE OPERATIONS WITH AI: A CASE FOR BUSINESS VALUEIJMIT JOURNAL
Artificial Intelligence (AI) has rapidly become a critical technology for businesses seeking to improve
efficiency and profitability. One area where AI is proving particularly impactful is in service operations
management, where it is used to create AI-powered service operations (AIServiceOps) that deliver highvalue services to customers. AIServiceOps involve the use of AI to automate and optimize various business
processes, such as customer service, sales, marketing, and supply chain management. The rapid
development of Artificial Intelligence has prompted many changes in the field of Information Technology
(IT) Service Operations. IT Service Operations are driven by AI, i.e., AIServiceOps. AI has empowered
new vitality and addressed many challenges in IT Service Operations. However, there is a literature gap on
the Business Value Impact of Artificial intelligence (AI) Powered IT Service Operations. It can help IT
build optimized business resilience by creating value in complex and ever-changing environments as
product organizations move faster than IT can handle. So, this research paper examines how AIServiceOps
creates business value and sustainability, basically how AIServiceOps makes the IT staff liberation from a
low-level, repetitive workout and traditional IT practices for a continuously optimized process. One of the
research objectives is to compare Traditional IT Service Operations with AIServiceOPs. This paper
provides the basis for how enterprises can evaluate AIServiceOps and consider it a digital transformation
tool. The paper presents a case study of a company that implemented AI-powered service operations
(AIServiceOps) and analyzes the resulting business outcomes. The study shows that AIServiceOps can
significantly improve service delivery, reduce response times, and increase customer satisfaction.
Furthermore, it demonstrates how AIServiceOps can deliver substantial cost savings, such as reducing
labor costs and minimizing downtime.
DESIGNING A FRAMEWORK FOR ENHANCING THE ONLINE KNOWLEDGE-SHARING BEHAVIOR OF ...IJMIT JOURNAL
The main objective of this paper is to identify the factors that influence academic staff's digital knowledgesharing behaviors in Ethiopian higher education. A structural equation model was used to validate the
research framework using survey data from 210 respondents. The collected data has been analyzed using
Smart PLS software. The results of the study show that trust, self-motivation, and altruism are positively
related to attitude. Contrary to our expectations, knowledge technology negatively affects attitude.
However, reward systems and empowerment by leaders are significantly associated with knowledgesharing intentions.Knowledge-sharing intention, in turn, was significantly related to digital knowledgesharing behavior. The contributions of this study are twofold. The framework may serve as a roadmap for
future researchers and managers considering their strategy to enhance digital knowledge sharing in HEI.
The findings will benefit academic staff and university administrations.The study will also help academic
staff enhance their knowledge-sharing practices.
BUILDING RELIABLE CLOUD SYSTEMS THROUGH CHAOS ENGINEERINGIJMIT JOURNAL
Cloud computing systems need to be reliable so that they can be accessed and used for computing at any
given point in time. The complex nature of cloud systems is the motivation to conduct research in novel
ways of ensuring that cloud systems are built with reliability in mind. In building cloud systems, it is
expected that the cloud system will be able to deal with high demands and unexpected events that affect the
reliability and performance of the system.
In this paper, chaos engineering is considered a heuristic method that can be used to build reliable cloud
systems. Chaos engineering is aimed at exposing weaknesses in systems that are in production. Chaos
engineering will help identify system weaknesses and strengths when a system is exposed to unexpected
knocks and shocks while it is in production.
Chaos engineering allows system developers and administrators to get insights into how the cloud system
will behave when it is exposed to unexpected occurrences.
A REVIEW OF STOCK TREND PREDICTION WITH COMBINATION OF EFFECTIVE MULTI TECHNI...IJMIT JOURNAL
It is important for investors to understand stock trends and market conditions before trading stocks. Both
these capabilities are very important for an investor in order to obtain maximized profit and minimized
losses. Without this capability, investors will suffer losses due to their ignorance regarding stock trends
and market conditions. Technical analysis helps to understand stock prices behavior with regards to past
trends, the signals given by indicators and the major turning points of the market price. This paper reviews
the stock trend predictions with a combination of the effective multi technical indicator strategy to increase
investment performance by taking into account the global performance and the proposed combination of
effective multi technical indicator strategy model.
NETWORK MEDIA ATTENTION AND GREEN TECHNOLOGY INNOVATIONIJMIT JOURNAL
This paper will provide a novel empirical study for the relationship between network media attention and
green technology innovation and examine how network media attention can ease financing constraints. It
collected data from listed companies in China's heavy pollution industry and performed rigorous
regression analysis, in order to innovatively explore the environmental governance functions of the media.
It found that network media attention significantly promotes green technology innovation. By analyzing the
inner mechanism further, it found that network media attention can promote green innovation by easing
financing constraints. Besides, network media attention has a significant positive impact on green invention
patents while not affecting green utility model patents.
INCLUSIVE ENTREPRENEURSHIP IN HANDLING COMPETING INSTITUTIONAL LOGICS FOR DHI...IJMIT JOURNAL
Information System (IS) research advocates employing collaborative and loose coupling strategies to address contradictory issues to address diversified actors’ interests than the prescriptive and unilateral Information Technology (IT) governance mechanisms’, yet it is rarely depicting how managers employ these strategies in Health Information System (HIS) implementation, particularly in a resource-constrained setting where IS implementation activities have highly relied on multiple international organizations resources. This study explored how managers in resource-constrained settings employ collaborative IT governance mechanisms in the case of District Health Information System 2 (DHIS2) adoption with an interpretative case study approach and the institutional logic concept. The institutional logic concept was used to identify the major actors’ logics underpinning the DHIS2 adoption. The study depicted the importance of high-level officials' distance from the dominant systemic logic to consider new alternative, and to employ inclusive IT governance mechanisms which separated resource from the system that facilitated stakeholders’ collaboration in DHIS2 adoption based on their capacity and interest.
DEEP LEARNING APPROACH FOR EVENT MONITORING SYSTEMIJMIT JOURNAL
With an increasing number of extreme events and complexity, more alarms are being used to monitor
control rooms. Operators in the control rooms need to monitor and analyze these alarms to take suitable
actions to ensure the system’s stability and security. Security is the biggest concern in the modern world. It
is important to have a rigid surveillance that should guarantee protection from any sought of hazard.
Considering security, Closed Circuit TV (CCTV) cameras are being utilized for reconnaissance, but these
CCTV cameras require a person for supervision. As a human being, there can be a possibility to be tired
off in supervision at any point of time. So, we need a system to detect automatically. Thus, we came up with
a solution using YOLO V5. We have taken a data set and used robo-flow framework to enhance the existing
images into numerous variations where it will create a copy of grey scale image, a copy of its rotation and
a copy of its blurred version which will be used to get an enlarged data set. This work mainly focuses on
providing a secure environment using CCTV live footage as a source to detect the weapons. Using YOLO
algorithm, it divides an image from the video into grid system and each grid detects an object within itself
MULTIMODAL COURSE DESIGN AND IMPLEMENTATION USING LEML AND LMS FOR INSTRUCTIO...IJMIT JOURNAL
Traditionally, teaching has been centered around classroom delivery. However, the onslaught of the
COVID-19 pandemic has cultivated usage of technology, teaching, and learning methodologies for course
delivery. We investigate and describe different modes of course delivery that maintain the integrity of
teaching and learning. This paper answers to the research questions: 1) What course delivery method our
academic institutions use and why? 2) How can instructors validate the guidelines of the institutions? 3)
How courses should be taught to provide student learning outcomes? Using the Learning Environment
Modeling Language (LEML), we investigate the design and implementation of courses for delivery in the
following environments: face-to-face, online synchronous, asynchronous, hybrid, and hyflex. A good
course design and implementation are key components of instructional alignment. Furthermore, we
demonstrate how to design, implement, and deliver courses in synchronous, asynchronous, and hybrid
modes and describe our proposed enhancements to LEML.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
COLLEGE BUS MANAGEMENT SYSTEM PROJECT REPORT.pdfKamal Acharya
The College Bus Management system is completely developed by Visual Basic .NET Version. The application is connect with most secured database language MS SQL Server. The application is develop by using best combination of front-end and back-end languages. The application is totally design like flat user interface. This flat user interface is more attractive user interface in 2017. The application is gives more important to the system functionality. The application is to manage the student’s details, driver’s details, bus details, bus route details, bus fees details and more. The application has only one unit for admin. The admin can manage the entire application. The admin can login into the application by using username and password of the admin. The application is develop for big and small colleges. It is more user friendly for non-computer person. Even they can easily learn how to manage the application within hours. The application is more secure by the admin. The system will give an effective output for the VB.Net and SQL Server given as input to the system. The compiled java program given as input to the system, after scanning the program will generate different reports. The application generates the report for users. The admin can view and download the report of the data. The application deliver the excel format reports. Because, excel formatted reports is very easy to understand the income and expense of the college bus. This application is mainly develop for windows operating system users. In 2017, 73% of people enterprises are using windows operating system. So the application will easily install for all the windows operating system users. The application-developed size is very low. The application consumes very low space in disk. Therefore, the user can allocate very minimum local disk space for this application.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
Contact with Dawood Bhai Just call on +92322-6382012 and we'll help you. We'll solve all your problems within 12 to 24 hours and with 101% guarantee and with astrology systematic. If you want to take any personal or professional advice then also you can call us on +92322-6382012 , ONLINE LOVE PROBLEM & Other all types of Daily Life Problem's.Then CALL or WHATSAPP us on +92322-6382012 and Get all these problems solutions here by Amil Baba DAWOOD BANGALI
#vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore#blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #blackmagicforlove #blackmagicformarriage #aamilbaba #kalajadu #kalailam #taweez #wazifaexpert #jadumantar #vashikaranspecialist #astrologer #palmistry #amliyaat #taweez #manpasandshadi #horoscope #spiritual #lovelife #lovespell #marriagespell#aamilbabainpakistan #amilbabainkarachi #powerfullblackmagicspell #kalajadumantarspecialist #realamilbaba #AmilbabainPakistan #astrologerincanada #astrologerindubai #lovespellsmaster #kalajaduspecialist #lovespellsthatwork #aamilbabainlahore #Amilbabainuk #amilbabainspain #amilbabaindubai #Amilbabainnorway #amilbabainkrachi #amilbabainlahore #amilbabaingujranwalan #amilbabainislamabad
Quality defects in TMT Bars, Possible causes and Potential Solutions.PrashantGoswami42
Maintaining high-quality standards in the production of TMT bars is crucial for ensuring structural integrity in construction. Addressing common defects through careful monitoring, standardized processes, and advanced technology can significantly improve the quality of TMT bars. Continuous training and adherence to quality control measures will also play a pivotal role in minimizing these defects.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
TECHNICAL TRAINING MANUAL GENERAL FAMILIARIZATION COURSEDuvanRamosGarzon1
AIRCRAFT GENERAL
The Single Aisle is the most advanced family aircraft in service today, with fly-by-wire flight controls.
The A318, A319, A320 and A321 are twin-engine subsonic medium range aircraft.
The family offers a choice of engines
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Maede Kiani Sarkaleh, Mehregan Mahdavi and Mahsa Baniardalan
1. International Journal of Managing Information Technology (IJMIT) Vol.4, No.2, May 2012
DOI : 10.5121/ijmit.2012.4202 13
DESIGNING A TOURISM RECOMMENDER SYSTEM
BASED ON LOCATION, MOBILE DEVICE AND USER
FEATURES IN MUSEUM
MAEDE KIANI SARKALEH, MEHREGAN MAHDAVI AND MAHSA BANIARDALAN
Department of Computer Engineering, University of Guilan, Rasht, Iran
maedeh.kiani@gmail.com, mahdavi@guilan.ac.ir, mahsa_ardalan@yahoo.com
ABSTRACT
Today, mobile devices are widely used by many tourists. They can use mobile for accessing information
about all sightseeing around the world. On the other hand, it seems essential to personalize the content due
to diversity of learners and variation of the tools they use. On the whole, the goal for personalization is to
suggest a collection of comprehensive activities, taking into consideration factors such as location, user
preferences and interests and so on. One of the applications of recommender systems is in tourism industry.
Mobile devices can be used in sites such as museums. Demands of different people such as students,
tourists and ordinary people can be met in spite of their diverse features and preferences. The purpose of
this paper is to give a model which is able to recommend new locations to visitors in a museum while the
visitor is given essential information about the certain features of the suggested site.
KEYWORDS
Recommender System, Location, Content Personalization, Mobile Device, User features
1. INTRODUCTION
Mobile devices have removed the location limitation such that one can personalize and suggest
content in suitable form to him or her while considering the environment where the person is. For
example, the tool can be used to obtain updated information about sightseeing around the world.
The information can be shared with other users interactively. There are certain challenges in this
area such as lack of an efficient model, diversity of information and the reality that the
information is not collected in a central server [1].
Personalization process is fulfilled using the information obtained from learner. On the whole,
the goal for personalization is to suggest a collection of comprehensive activities taking into
consideration factors such as location, user preferences and interest and so on [2]. Personalization
is performed through two methods: adjusting the learning services with learner’s features such as
learning methods, demands, situations, efficiencies, preferences and criteria; learning system
conformation with learner’s surroundings. Interrelation between user and user with the nearest
neighborhood algorithm is used by most personalized systems. User-user interrelation is resulted
from statistics and figures which signify the interrelations between variants and it is used to
measure the model efficiency. In recommender systems, the interrelation is used to measure the
rate of similarities between two users and to identify the users who are expected to be
categorized.
2. International Journal of Managing Information Technology (IJMIT) Vol.4, No.2, May 2012
14
As you know, there are a lot of diversities for mobile systems and applications of awareness of
content. Awareness of content is an important feature for the recommender systems. Some
aspects have been mentioned by Shilit et al: “Where are you? With whom? Which sources are
near you? “Taking into account the traditional location of the user and his or her companions and
how the near sources are obtained, significantly increases the applications of mobile system. In
[13], instead of traditional methods which use only two dimensions of user and product,
multidimensional methods are used.
When tourists arrive in a country, they need to pay for such things as food, hotel, transport,
entertainment, museum and sightseeing visit. The currency the tourists bring into the visited
country, leads to economic vigorous grow or so called covert export. Museum is one of tourist
attractive sites in which learning content can be represented as an environment adjusted and
suitable personalized form using advanced technologies such as mobile, laptop, PDA and so on in
order that the tourist can be attracted to the system and other museums as well.
The organization of this paper is as follows: in Section two, former investigations are presented.
Section three gives the suggested model in detail. The model is evaluated in Section four. The
conclusion is given in the Section five.
2. LITERATURE REVIEW
In mid 1990s, the investigation about recommender systems began, focusing clearly on pricing.
The issues were lowered by user defined formulas for estimated rates. The estimations were
performed based on user defined ratings for items and other conventional information. Therefore,
items with the highest rates were suggested to user. C signifies as all users and S is defined as all
possible items such as books, film, restaurants and so on that can be suggested to user. S can be
very extensive, amounting to hundreds, thousands or millions items for any user. For example,
book or CD suggested items may reach to millions.
Collaborative filtering process for suggestion is the advanced technology now used in
recommender systems leading to simpler and more quickly suggestions. Former recommender
systems used collaborative filtering to predict a certain product rating in view of a certain user.
There are two types of collaborative filtering: user-defined and item –based. The item-based
collaborative filtering focuses on acquired items similarities rather than users‘ and is now
prevalent and has high scalability and is suitable for great data collections [4].
Content-based filtering can also be used to suggest the present products which are preferable in
view point of user. These systems use profiles which have been obtained from user. Profile
represents information about the user and her or his interests. User’s interests are measured based
on items ratings. The search engine processes the former ratings of user along with unrated ones
and it compares the similar features and finally suggested ones are presented [5].
Some of existing products are not purchased regularly so their purchase is regarded as very risky
(such as financial services, car, electronic instruments and tourist services). In this case,
recommender system so called knowledge-based recommender needs to comprehend deeply the
user’s demands to suggest helpful and accurate cases to the user [6]. Each type of recommender
system benefits a certain advantages and disadvantages. Hybrid recommender system consists of
two or more types of recommender systems to remove the disadvantages and to increase
efficiency, capability and reliability of suggestion [7]. Many tourist guidance systems use
content-based models. The system designed in [8] uses the information which is collected based
on user’s preferences and its content information includes location, elapsed time in the distance,
the direction of the selected path, personal preferences and various user systems. Buchman and
Hinze designed a system which suggested information about the sightseeing to tourists [9] and its
3. International Journal of Managing Information Technology (IJMIT) Vol.4, No.2, May 2012
15
content information included user location, present time, interests and such information about
sightseeing as their locations, types and similarities. Other system called Cyber guide has been
designed for tourism industry [10]. This system acts as human guide and uses PDA and GPS to
give service to tourists in a site. Other system designed in [1], called Murshid uses Google Map as
a visual guide. It is a content intelligent system which uses user location information, his or her
interests, job and time schedule. Location-based and content intelligent recommender system
uses content information such as location, time and so on and it is applied in restaurants [11, 12,
and 13], tourism industry [14] and commercial systems. Many investigations have been
performed about content to suggest suitable services to users and certain recommender systems
are introduced in brief in table 1.
Table 1. Some existing context-aware recommender systems
MIT
Media
Lab
National
Tsing Hua
Univ.
Telematica
Institute
Fu-Jen
Univ.
Telematica
Institute
Murshid
Recommenda
tion type
Restaurant Restaurant
Travel
information
Commerci
al
Tourism
industry
Tourism
industry
Context
information
Location
Location,
Time,
Weather
Location,
Time,
Weather,
Shopping
list,
Schedule
Location,
Time,
Fare,
Contents
Location,
Time,
Weather,
Location,
profile,
Time, user
interaction
Recommenda
tion method
Interaction
between 2
agents
Search
after
requesting
Variable
prediction
strategy
Neural
network
learning
Variable
predictor
strategy
reasoning
engine,
J2ME
Device PDA, GPS
Pocket PC,
GPS
Mobile
phone, GPS
Mobile
hone
Mobile
phone, GPS
Mobile
phone,
GPS,
Google
map
3. CONTENT PERSONALIZATION
Although there are various features for personalization, we plan to deal with significant as well as
efficient ones such that their complications neither result in lower system speed in terms of real
time response to user nor it fails to meet the user’s essential needs.
Since museum visitors significant features for categorization are knowledge level, ethnic
language and more important of all, a lot of tools and instruments the visitors use to acquire the
contents of artistic works, so the recommender system must take these features into account. The
figure 1 shows the personalization process.
4. International Journal of Managing Information Technology (IJMIT) Vol.4, No.2, May 2012
16
Mobile learning
software
Personalization
system
History
log
priority
location
time
language
khnowledge
behavioral pattern
interest
Mocile device
Figure 1. The personalization process
3.1. Feature-Based Personalization
• Knowledge Level: The prevalent knowledge level of learner can be assessed by tests and
can be scored qualitatively (beginner, middle, advanced) and quantitatively (0-10). At the
beginning, the learner is not identified by the system and it needs to pose self- teaching
questions in order to identify the learner and to update the knowledge level of the learner
consecutively.
• The preferences and interests can be similarly categorized. If learner is low interested, the
system can give a general outline to the learner. If the learner is interested in the subject,
the system can present detailed information. It is noted that at the beginning, the interest
level of learner is null and it can be updated over time. The learner’s preferences show
how the learner desires to acquire the content (various multimedia such as audio, video,
animation, text and so on which can be represented automatically).
• The language of visitor: The exhibition content must be adjusted to the native language of
foreign visitors (English, Arabic, French, etc.)
3.2. Personalization based on User’s Mobile Device
Today, various mobile technologies are consecutively growing all around the world. A lot of
electronic services can be noted with many applications [16] including network-based mobile
learning, wireless connections and mobile devices such as notebooks, mobile phone, personal
communication system (PCS) and personal digital assistant (PDA) [17]. The features of mobile
devices include mobility, independency, singularity, and accessibility. These features have
changed learning model. The singularity of mobile learning allows learner to personalize the
learning in accurate time and place and to enrich and diversify the learning content as much as
possible.
In a museum, visitors bring diverse mobile devices with themselves so the exhibition must be
represented in diverse personalized forms such as audio, video, text and animation, compatible
5. International Journal of Managing Information Technology (IJMIT) Vol.4, No.2, May 2012
17
with visitor’s mobile devices. Other possible compatibilities include multilingual support, diverse
power consumption in Watt, the scale of exhibition screen, multimedia formats support (text,
audio and video), search capability, user interaction compatibility,, processing rate, RAM and its
speed, connection technologies such as Bluetooth, 3G, Wi-Fi, IrDA and GPRS. A visitor who
uses a regular mobile phone is able to receive information in animation format but only text
format is available for her or him; however, another visitor who uses IPoD is able to receive the
information about e.g. an animal life in video and animation formats, not available in the
museum.
3.2. Personalization based on user location
Location-based services are value added ones in which position information is used to present
diverse and interesting services to user including emergency services, vehicle navigation systems,
tourist broadcasting services, searching in country- wide or urban sites data banks using map.
Geographic Position System (GPS) works based on satellite tracking and allows user to locate
every point on the globe accurately. Mobile learning can be conducted through tracking by GPS.
The GPS data can define three concepts: users, locations and activities in a certain site [18].
Another facility is communication network (BSC and BTS).BTS is responsible for exchanging
radio waves with mobile unit as well as control and exchange data with BSC. BTS consists of
independent transceivers, providing aerial and radio connection with mobile unit. BTS is the
smallest unit of service provider in mobile radio network, supporting the certain region of the
network called cell. BTS is designed to support higher radio coverage in roads or where the signal
is weak and to meet traffic needs and its regular range in a smooth region is 30-35 KMs but it is
20 KMs in practice.
Radio Frequency Identification (RFID) is one of modern tracking technologies to locate user.
This system identifies mobile and static objects by radio waves. In this new method, certain tags
are used to store data. The data would be restored when needed [19]. The smart tag can be
embedded inside electronic and non electronic products, animals and human body. The tag can be
identified via transceiver waves in any time and place. RFID is now used for tracking vehicles,
people, objects, security, transaction register and so on.
Google Map is another method in which the map can be efficiently downloaded and stored for
future use. In its new versions, maps can be illustrated two and three dimensionally and it is
possible to search the locations, to mark the interested points on the map, to give support for such
services as Street View and My Tracks and audio guide.
4. THE SUGGESTED MODEL (PROCESS OF RECOMMENDING NEW SITE TO
VISIT IN A MUSEUM)
Tourist attract is regarded as very significant and essential target for any state. Mobile devices can
be used in such places as museums thanks to new technologies and the needs of different groups
of people such as students, tourists, and ordinary people can be met via these technologies.
GPS can be used to track the visitors inside the museum and three concepts (user, location and
activities) can be derived. One can usually see a lot of artistic works in a museum in many parts
and shelves belonging to diverse fields of science. When a visitor visits a museum, recommender
system must have a clear understanding of what the visitor needs to know as a learner and what
seems attractive to the visitor and which part of the museum would be interesting for the visitor
and should be offered to him or her.
Three behaviors of visitor (the visited place, preference for visit and amount of time spent in each
visit) are identified after visitor visited the artistic works. This process is conducted via GPS. The
6. International Journal of Managing Information Technology (IJMIT) Vol.4, No.2, May 2012
18
collected data derived from the process is stored in a so called former visitors’ data base in order
to be used for later visitors. Recommender system suggests a place to next visitor based on former
similar existing data.
Figure 2. Process of suggesting new place to visit
Figure 2 shows the process of recommending a visitor a new place to visit. The suggested model
steps are as follows:
• Step 1. Visitor identification: Content manager module is responsible for collecting
content. The existing user’s content must be delivered to the next step for process. The
time and date are also restored from the mobile devices. At first, information about visitor
is collected in order that improved personalization can be done efficiently. Figure 2
shows the content used in the model.
time
Longitude
Latitude
Khnowledge
interest
language
memory
Throughput
screen
size
Figure 3. Content information
• Step 2. Comparison: It has two sections. 1. Storing the visitor information: The data
derived from the user is stored implicitly in data base with lowest interruption for user.
Recommender system can suggest next location to visit based on this data. 2. Comparing
visitor’s information with the information of former visitors in data base and suggesting
next location to visit based on former and later visitors similarities.
• Step 3. Recommend feedback: The question is whether the suggestion has been
acceptable for user or not. The answer would be available when the suggested place is
compared with the visited one and then the quality of system can be evaluated on this
basis.
7. International Journal of Managing Information Technology (IJMIT) Vol.4, No.2, May 2012
19
5. ASSESSMENT
It is important to select suitable factors for evaluation such as cross assessment method, accuracy
and restoration. Cross assessment method is used to determine the quality of a classifying tool
and some learning data is used as a test set. For example, 90% of data is used as learning data and
the remaining 10% is used to test the method. Accuracy is measured based on the number of
accurately classified samples. The accuracy rate and the restoration rate for each classifier are
assessed after learning and testing processes and identifying the class of each sample. The
accuracy and restoration rates can be measured. The performance of classifier is judged based on
the rate of any class. In fact, higher accuracy and restoration in restoring data are used to measure
accuracy of various algorithms as well as for classifying methods.
First certain data is intended as learning data for the system and then the suggested model is
assessed. Another data set is intended for testing the system. It is essential to collect all data to
find whether the next visited place would be the same suggested one by the system or not.
6. CONCLUSIONS
In this paper we explored certain recommender systems. Then, a model was suggested as a
recommender system to offer visitors a new location to visit. Due to diversity of visitors in terms
of their mobile device and variation of networks, content personalization is essential. Location-
based services use GPS facility to track people based on the data derived about three concepts of
user, location and activities in a certain site. Then, the suggested model can be used for visitors in
practice.
REFERENCES
[1] L. Hajesmaeili, Z. Borhanifard & M. araste (2010) E Commerce, Tehran, adabestan.
[2] A. A. Economides, (2008) "Personalization for Location-Based E-Learning", The Second
International Conference on Next Generation Mobile Applications, Services, and Technologies, pp.
247-253.
[3] A. A. Economides (2009) "Requirements of mobile learning applications", International Journal of
Innovation and Learning, Vol. 5, No. 5, pp. 457-479.
[4] T. H. Brown (2003)"The role of m-learning in the future of e-learning in Africa?", presentation at the
21st
ICDE World Conference.
[5] A. Echtibi, M. J. Zemerly, J. Berri (2009) "A Service-Based Mobile Tourist Advisor", International
Journal of Computer Information Systems and Industrial Management Applications (IJCISIM), Vol.1,
pp.177-187.
[6] A. K. Dey, G. B. Abowd (1998) "A Conceptual Framework and a Tool Kit for Supporting The rapid
Prototyping of Context aware Application".
[7] A. Jappinen, J. Nummela, T. Vainio, M. Ahonen (2004) "Adaptive Mobile Learning Systems – The
Essential Questions from the Design Perspective", In the Proceedings of MLearn2004, Roma, Italy,
pp.109-112.
[8] M. Yudelson, T. Gavrilova, P. Brusilovsky (2005) "Towards user modeling meta-ontology", Proc. of
10th International User Modeling Conference, Springer Verlag, pp. 448-452.
[9] A. A. Economides (2008) "Context-aware mobile learning", the open Knowledge Society, A computer
Science and Information Systems Manifesto, pp. 213-220, September 24-26.
[10] Kinshuk, M. Chang, S. Graf, G. Yang (2009) "Adaptivity and Personalization in Mobile Learning",
Annual Meeting of the American Educational Research Association, San Diego, CA, April 13–17.
8. International Journal of Managing Information Technology (IJMIT) Vol.4, No.2, May 2012
20
[11] V. W. Zheng, B. Cao, Y. Zheng, X. Xie, Q. Yang (2010) "Collaborative Filtering Meets Mobile
Recommendation: A User-centered Approach", Association for the Advancement of Artificial
Intelligence (www.aaai.org).
[12] T. Karygiannis, B. Eydt, G. Barber, L. Bunn, T. phillip (2007) "Guidance for Securing Radio
Frequency Identification Systems" National Institute of Standards and Technology Gaithersburg.
[13] K.S. Huang, Tang (2008) "S.M., "RFID Applications Strategy and Deployment in Bike Renting
System", Department of Information Management, National Yunlin University of Science and
Technology, No. 123, University Road, Douliou, Yunlin, Taiwan, R. 0. C.
[14] J. Gavin (2007) "Mobile Phone Web Users Nearly Equal PC Based Internet Users in Japan",
comScore. From http://www.comscore.com.
[15] B. Schilit, N. Adams, R.Want (1994) "Context-aware computing applications". IEEE Workshop on
Mobile Computing Systems and Applications (WMCSA'94), Santa Cruz, CA, US: 89-101.
[16] M. Al Ali, J. Berri, J. Zemerly (2008) “Context-Aware Mobile Muslim Companion”, Proc. of the 5th
Int. Conference on Soft Computing as a Transdisciplinary Science and Technology, Context Aware
Mobile Learning Workshop, Cergy Pontoise, France, pp. 553-558, 27 Oct – 1.
[17] A. Pashtan, R. Blattler, A. Heusser, P. Scheuermann (2003) “CATIS: A Context-Aware Tourist
Information System”, Proceedings of the 4th International Workshop on Mobile Computing, Rostok,
June, pp.1-8.
[18] L A. Hinze, G. Buchanan (2005) “Context-awareness in Mobile Tourist Information Systems:
Challenges for User Interaction”, Int. Workshop on Context in Mobile HCI, Salzburg.
[19] A. Garcia-Crespo, et al. (2009) “SPETA: Social pervasive e-Tourism advisor”, Telematics and
Informatics, vol. 26, pp. 306-315.
[20] G. Tewari, J. Youll, P.Maes (2003) “Personalized location-based brokering using an agent-base
intermediary architecture”, Decision Support Systems 34, pp. 127–137.
[21] H. Tung, V. Soo (2004) “A personalized restaurant recommender agent for mobile e-service” IEEE
International Conference on e-Technology, e-Commerce and e-Service (EEE’04), pp. 259–262.
[22] L M. Park, J. Indulska, and S. Cho (2007) “Location-Based Recommendation System Using Bayesian
User's Preference Model in Mobile Devices”, LNCS 4611, pp. 1130–1139.
[23] M. Setten, S. Pokraev, J. Koolwaaij (2004) “Context-aware recommendations in the mobile tourist
application COMPASS” AH2004, pp. 235–244.
[24] S. Yuan, Y. Tsao (2003) “A recommendation mechanism for contextualized mobile advertising”,
Expert Systems with Applications 24, pp. 399–414.
[25] T. Horozov, N. Narasimhan, V. Vasudevan (2006) “Using location for personalized POI
recommendations in mobile environments”, SAINT 2006, pp. 124–129.
[26] R. J. Mooney, L. Roy (2000) “Content-based book recommending using learning for text
categorization”, Proceeding of the fifth ACM conference on Digital libraries Publisher, ACM Press,
pp. 195-204.
[27] Robin Burke (2000) “Knowledge-based recommender systems”, Encyclopedia of Library and
Information Systems.
[28] Robin Burke (2002) “Hybrid recommender systems: Survey and experiments”, User Modeling and
User-Adapted Interaction, Vol. 12, No. 4, pp. 331–370.
[29] G. Adomavicius, R. Sankaranarayanan, S. Sen and A. Tuzhilin (2005) “Incorporating Contextual
Information in Recommender Systems Using a Multidimensional Approach”, ACM Transactions on
Information Systems, Vol. 23, No. 1, pp. 103-145.
[30] A. Felfernig, S. Gordea, D. Jannach, E. Teppan, and M. Zanker “A Short Survey of Recommendation
Technologies in Travel and Tourism”, ÖGAI Journal, Vol. 25 No. 2.
9. International Journal of Managing Information Technology (IJMIT) Vol.4, No.2, May 2012
21
[31] J. Wolf, C. Aggarwal, K. Wu,., & P. Yu, (1999) “Horting Hatches an Egg: A New Graph-Theoretic
Approach to Collaborative Filtering”, In Proceedings of ACM SIGKDD International Conference on
Knowledge Discovery & Data Mining, San Diego, CA.
[32] J. Breese, D. Heckerman & C. Kadie (1998) “Empirical Analysis of Predictive Algorithms for
Collaborative Filtering”, In Proceedings of the 14th
Conference on Uncertainty in Artificial
Intelligence (UAI-98), pp 43-52.
[33] B. Sarwar, G. Karypis, J.A. Konstan, & J. Reidl, (2001) “Item-based Collaborative Filtering
Recommendation Algorithms”, Proceedings of the Tenth International Conference on World Wide
Web, pp. 285 - 295.