On World Wide Web various kind of content are generated in huge amount, so to give relevant result to user web recommendation become important part of web application. On web different kind of web recommendation are made available to user every day that includes Image, Video, Audio, query suggestion and web page. In this paper we are aiming at providing framework for web page recommendation. 1) First we describe the basics of web mining, types of web mining. 2) Details of each web mining technique.3)We propose the architecture for the personalized web page recommendation.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Recommendation generation by integrating sequential pattern mining and semanticseSAT Journals
Abstract As the Internet usage keeps increasing, the number of web sites and hence the number of web pages also keeps increasing. A recommendation system can be used to provide personalized web service by suggesting the pages that are likely to be accessed in future. Most of the recommendation systems are based on association rule mining or based on keywords. Using the association rule mining the prediction rate is less as it doesn’t take into account the order of access of the web pages by the users. The recommendation systems that are key-word based provides lesser relevant results. This paper proposes a recommendation system that uses the advantages of sequential pattern mining and semantics over the association rule mining and keyword based systems respectively. Keywords: Sequential Pattern Mining, Taxonomy, Apriori-All, CS-Mine, Semantic, Clustering
An Enhanced Approach for Detecting User's Behavior Applying Country-Wise Loca...IJSRD
The development of the web in past few years has created a lot of challenge in this field. The new work in this field is the search of the data in a search tree pattern based on tree. Various sequential mining algorithms have been devoloped till date. Web usage mining is used to operate the web server logs, that contains the navigation history of the user. Recommendater system is explained properly with the explanation of whole procedure of the recommendater system. The search results of the data leads to the proper ad efficient search. But the problem was the time utilization and the search results generated from them. So, a new local search algorithm is proposed for country-wise search that makes the searching more efficient on local results basis. This approach has lead to an advancement in the search based methods and the results generated.
Comparable Analysis of Web Mining Categoriestheijes
Web Data Mining is the current field of analysis which is a combination of two research area known as Data Mining and World Wide Web. Web Data Mining research associates with various research diversities like Database, Artificial Intelligence and Information redeem. The mining techniques are categorized into various categories namely Web Content Mining, Web Structure Mining and Web Usage Mining. In this work, analysis of mining techniques are done. From the analysis it has been concluded that Web Content Mining has unstructured or semi- structure view of data whereas Web Structure Mining have linked structure and Web Usage Mining mainly includes interaction.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Recommendation generation by integrating sequential pattern mining and semanticseSAT Journals
Abstract As the Internet usage keeps increasing, the number of web sites and hence the number of web pages also keeps increasing. A recommendation system can be used to provide personalized web service by suggesting the pages that are likely to be accessed in future. Most of the recommendation systems are based on association rule mining or based on keywords. Using the association rule mining the prediction rate is less as it doesn’t take into account the order of access of the web pages by the users. The recommendation systems that are key-word based provides lesser relevant results. This paper proposes a recommendation system that uses the advantages of sequential pattern mining and semantics over the association rule mining and keyword based systems respectively. Keywords: Sequential Pattern Mining, Taxonomy, Apriori-All, CS-Mine, Semantic, Clustering
An Enhanced Approach for Detecting User's Behavior Applying Country-Wise Loca...IJSRD
The development of the web in past few years has created a lot of challenge in this field. The new work in this field is the search of the data in a search tree pattern based on tree. Various sequential mining algorithms have been devoloped till date. Web usage mining is used to operate the web server logs, that contains the navigation history of the user. Recommendater system is explained properly with the explanation of whole procedure of the recommendater system. The search results of the data leads to the proper ad efficient search. But the problem was the time utilization and the search results generated from them. So, a new local search algorithm is proposed for country-wise search that makes the searching more efficient on local results basis. This approach has lead to an advancement in the search based methods and the results generated.
Comparable Analysis of Web Mining Categoriestheijes
Web Data Mining is the current field of analysis which is a combination of two research area known as Data Mining and World Wide Web. Web Data Mining research associates with various research diversities like Database, Artificial Intelligence and Information redeem. The mining techniques are categorized into various categories namely Web Content Mining, Web Structure Mining and Web Usage Mining. In this work, analysis of mining techniques are done. From the analysis it has been concluded that Web Content Mining has unstructured or semi- structure view of data whereas Web Structure Mining have linked structure and Web Usage Mining mainly includes interaction.
In this world of information technology, everyone has the tendency to do business electronically. Today
lot of businesses are happening on World Wide Web (WWW), it is very important for the website owner to
provide a better platform to attract more customers for their site. Providing information in a better way is
the solution to bring more customers or users. Customer is the end-user, who accessing the information
in a way it yields some credit to the web site owners. In this paper we define web mining and present a
method to utilize web mining in a better way to know the users and website behaviour which in turn
enhance the web site information to attract more users. This paper also presents an overview of the
various researches done on pattern extraction, web content mining and how it can be taken as a catalyst
for E-business.
BIDIRECTIONAL GROWTH BASED MINING AND CYCLIC BEHAVIOUR ANALYSIS OF WEB SEQUEN...ijdkp
Web sequential patterns are important for analyzing and understanding users’ behaviour to improve the
quality of service offered by the World Wide Web. Web Prefetching is one such technique that utilizes
prefetching rules derived through Cyclic Model Analysis of the mined Web sequential patterns. The more
accurate the prediction and more satisfying the results of prefetching if we use a highly efficient and
scalable mining technique such as the Bidirectional Growth based Directed Acyclic Graph. In this paper,
we propose a novel algorithm called Bidirectional Growth based mining Cyclic behavior Analysis of web
sequential Patterns (BGCAP) that effectively combines these strategies to generate prefetching rules in the
form of 2-sequence patterns with Periodicity and threshold of Cyclic Behaviour that can be utilized to
effectively prefetch Web pages, thus reducing the users’ perceived latency. As BGCAP is based on
Bidirectional pattern growth, it performs only (log n+1) levels of recursion for mining n Web sequential
patterns. Our experimental results show that prefetching rules generated using BGCAP is 5-10% faster for
different data sizes and 10-15% faster for a fixed data size than TD-Mine. In addition, BGCAP generates
about 5-15% more prefetching rules than TD-Mine.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Identifying the Number of Visitors to improve Website Usability from Educatio...Editor IJCATR
Web usage mining deals with understanding the Visitor’s behaviour with a Website. It helps in understanding the concerns
such as present and future probability of every website user, relationship between behaviour and website usability. It has different
branches such as web content mining, web structure and web usage mining. The focus of this paper is on web mining usage patterns of
an educational institution web log data. There are three types of web related log data namely web access log, error log and proxy log
data. In this paper web access log data has been used as dataset because the web access log data is the typical source of navigational
behaviour of the website visitor. The study of web server log analysis is helpful in applying the web mining techniques.
A Review on Pattern Discovery Techniques of Web Usage MiningIJERA Editor
In the recent years with the development of Internet technology the growth of World Wide Web exceeded all expectations. A lot of information is available in different formats and retrieving interesting content has become a very difficult task. One possible approach to solve this problem is Web Usage Mining (WUM), the important application of Web Mining. Extracting the hidden knowledge in the log files of a web server, recognizing various interests of web users, discovering customer behavior while at the site are normally referred as the applications of web usage mining. In this paper we provide an updated focused survey on techniques of web usage mining.
IRJET-A Survey on Web Personalization of Web Usage MiningIRJET Journal
S.Jagan, Dr.S.P.Rajagopalan "A Survey on Web Personalization of Web Usage Mining", International Research Journal of Engineering and Technology (IRJET),Volume 2,issue-01 Mar-2015. e-ISSN:2395-0056, p-ISSN:2395-0072. www.irjet.net , published by Fast Track Publications
Abstract
Now a day, World Wide Web (www) is a rich and most powerful source of information. Day by day it is becoming more complex and expanding in size to get maximum information details online. However, it is becoming more complex and critical task to retrieve exact information expected by its users. To deal with this problem one more powerful concept is personalization which is becoming more powerful now days. Personalization is a subclass of information filtering system that seek to predict the 'ratings' or 'preferences' that a user would give to an items, they had not yet considered, using a model built from the characteristics of an item (content-based approaches or collaborative filtering approaches). Web mining is an emerging field of data mining used to provide personalization on the web. It consist three major categories i.e. Web Content Mining, Web Usage Mining, and Web Structure Mining. This paper focuses on web usage mining and algorithms used for providing personalization on the web.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
AN INTELLIGENT OPTIMAL GENETIC MODEL TO INVESTIGATE THE USER USAGE BEHAVIOUR ...ijdkp
The unexpected wide spread use of WWW and dynamically increasing nature of the web creates new
challenges in the web mining since the data in the web inherently unlabelled, incomplete, non linear, and
heterogeneous. The investigation of user usage behaviour on WWW is real time problem which involves
multiple conflicting measures of performance. These measures make not only computational intensive but
also needs to the possibility of be unable to find the exact solution. Unfortunately, the conventional methods
are limited to optimization problems due to the absence of semantic certainty and presence of human
intervention. In handling such data and overcome the limitations of conventional methodologies it is
necessary to use a soft computing model that can work intelligently to attain optimal solution.
Web Usage Mining: A Survey on User's Navigation Pattern from Web Logsijsrd.com
With an expontial growth of World Wide Web, there are so many information overloaded and it became hard to find out data according to need. Web usage mining is a part of web mining, which deal with automatic discovery of user navigation pattern from web log. This paper presents an overview of web mining and also provide navigation pattern from classification and clustering algorithm for web usage mining. Web usage mining contain three important task namely data preprocessing, pattern discovery and pattern analysis based on discovered pattern. And also contain the comparative study of web mining techniques.
Secure and Reliable Data Transmission in Generalized E-MailIJERA Editor
Email is a basic service for computer users, while email malware poses critical security threats. The technique of email-borne malware will be highly effective. Email malware focuses on modeling the propagation dynamics which is a fundamental technique for developing countermeasures to reduce email malware’s spreading speed and prevalence. Modern email malware exhibits two new features, reinjection and self-start. Reinjection is an infected user sends out malware copies whenever this user visits the malicious hyperlinks or attachments. Self-start refers to the behavior that malware starts to spread whenever compromised computers restart or certain files are visited. For address this problem, to derive a novel difference equation based analytical model by introducing a new concept of virtual dirty user. Propose a new analytical model to enhanced OLSR protocol which is a trust based technique to secure the OLSR nodes against the attack. The proposed solution called EOLSR is an enhancement of the basic OLSR routing protocol, which will be able to detect the presence of malicious nodes in the network.
Development And Implementation Of OFDM Transceiver For WLAN ApplicationsIJERA Editor
Multi-Carrier modulation is a technique for data transmission by multiplexing a low bit-rate data streams to modulated carriers into signal Wideband Carrier. Multi-Carrier transmission has a lot of useful properties such as delay-spread tolerance and spectrum efficiency that encourage their use in untethered broadband communication. OFDM is becoming the chosen modulation technique for wireless communications. OFDM is a multi-carrier modulation scheme with densely spaced sub-carriers that has gained a lot of popularity among the broadband community in the last few years. OFDM can provide large data rate with sufficient robustness to radio channel impairments. OFDM works on the principle of Orthogonality. The orthogonality between subcarriers which is at the core of OFDM modulation requires a perfect synchronization. OFDM has properties like high spectral efficiency, Resiliency to RF interference and Lower multi-path distortion. This work is concentrated in implementing both transmitter and receiver using Matlab software and also to verify whether the transmitted data is obtained at the receiver side. As we are using the OFDM technique we will be having bandwidth efficiency when compared to the normal FDM technique.
In this world of information technology, everyone has the tendency to do business electronically. Today
lot of businesses are happening on World Wide Web (WWW), it is very important for the website owner to
provide a better platform to attract more customers for their site. Providing information in a better way is
the solution to bring more customers or users. Customer is the end-user, who accessing the information
in a way it yields some credit to the web site owners. In this paper we define web mining and present a
method to utilize web mining in a better way to know the users and website behaviour which in turn
enhance the web site information to attract more users. This paper also presents an overview of the
various researches done on pattern extraction, web content mining and how it can be taken as a catalyst
for E-business.
BIDIRECTIONAL GROWTH BASED MINING AND CYCLIC BEHAVIOUR ANALYSIS OF WEB SEQUEN...ijdkp
Web sequential patterns are important for analyzing and understanding users’ behaviour to improve the
quality of service offered by the World Wide Web. Web Prefetching is one such technique that utilizes
prefetching rules derived through Cyclic Model Analysis of the mined Web sequential patterns. The more
accurate the prediction and more satisfying the results of prefetching if we use a highly efficient and
scalable mining technique such as the Bidirectional Growth based Directed Acyclic Graph. In this paper,
we propose a novel algorithm called Bidirectional Growth based mining Cyclic behavior Analysis of web
sequential Patterns (BGCAP) that effectively combines these strategies to generate prefetching rules in the
form of 2-sequence patterns with Periodicity and threshold of Cyclic Behaviour that can be utilized to
effectively prefetch Web pages, thus reducing the users’ perceived latency. As BGCAP is based on
Bidirectional pattern growth, it performs only (log n+1) levels of recursion for mining n Web sequential
patterns. Our experimental results show that prefetching rules generated using BGCAP is 5-10% faster for
different data sizes and 10-15% faster for a fixed data size than TD-Mine. In addition, BGCAP generates
about 5-15% more prefetching rules than TD-Mine.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Identifying the Number of Visitors to improve Website Usability from Educatio...Editor IJCATR
Web usage mining deals with understanding the Visitor’s behaviour with a Website. It helps in understanding the concerns
such as present and future probability of every website user, relationship between behaviour and website usability. It has different
branches such as web content mining, web structure and web usage mining. The focus of this paper is on web mining usage patterns of
an educational institution web log data. There are three types of web related log data namely web access log, error log and proxy log
data. In this paper web access log data has been used as dataset because the web access log data is the typical source of navigational
behaviour of the website visitor. The study of web server log analysis is helpful in applying the web mining techniques.
A Review on Pattern Discovery Techniques of Web Usage MiningIJERA Editor
In the recent years with the development of Internet technology the growth of World Wide Web exceeded all expectations. A lot of information is available in different formats and retrieving interesting content has become a very difficult task. One possible approach to solve this problem is Web Usage Mining (WUM), the important application of Web Mining. Extracting the hidden knowledge in the log files of a web server, recognizing various interests of web users, discovering customer behavior while at the site are normally referred as the applications of web usage mining. In this paper we provide an updated focused survey on techniques of web usage mining.
IRJET-A Survey on Web Personalization of Web Usage MiningIRJET Journal
S.Jagan, Dr.S.P.Rajagopalan "A Survey on Web Personalization of Web Usage Mining", International Research Journal of Engineering and Technology (IRJET),Volume 2,issue-01 Mar-2015. e-ISSN:2395-0056, p-ISSN:2395-0072. www.irjet.net , published by Fast Track Publications
Abstract
Now a day, World Wide Web (www) is a rich and most powerful source of information. Day by day it is becoming more complex and expanding in size to get maximum information details online. However, it is becoming more complex and critical task to retrieve exact information expected by its users. To deal with this problem one more powerful concept is personalization which is becoming more powerful now days. Personalization is a subclass of information filtering system that seek to predict the 'ratings' or 'preferences' that a user would give to an items, they had not yet considered, using a model built from the characteristics of an item (content-based approaches or collaborative filtering approaches). Web mining is an emerging field of data mining used to provide personalization on the web. It consist three major categories i.e. Web Content Mining, Web Usage Mining, and Web Structure Mining. This paper focuses on web usage mining and algorithms used for providing personalization on the web.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
AN INTELLIGENT OPTIMAL GENETIC MODEL TO INVESTIGATE THE USER USAGE BEHAVIOUR ...ijdkp
The unexpected wide spread use of WWW and dynamically increasing nature of the web creates new
challenges in the web mining since the data in the web inherently unlabelled, incomplete, non linear, and
heterogeneous. The investigation of user usage behaviour on WWW is real time problem which involves
multiple conflicting measures of performance. These measures make not only computational intensive but
also needs to the possibility of be unable to find the exact solution. Unfortunately, the conventional methods
are limited to optimization problems due to the absence of semantic certainty and presence of human
intervention. In handling such data and overcome the limitations of conventional methodologies it is
necessary to use a soft computing model that can work intelligently to attain optimal solution.
Web Usage Mining: A Survey on User's Navigation Pattern from Web Logsijsrd.com
With an expontial growth of World Wide Web, there are so many information overloaded and it became hard to find out data according to need. Web usage mining is a part of web mining, which deal with automatic discovery of user navigation pattern from web log. This paper presents an overview of web mining and also provide navigation pattern from classification and clustering algorithm for web usage mining. Web usage mining contain three important task namely data preprocessing, pattern discovery and pattern analysis based on discovered pattern. And also contain the comparative study of web mining techniques.
Secure and Reliable Data Transmission in Generalized E-MailIJERA Editor
Email is a basic service for computer users, while email malware poses critical security threats. The technique of email-borne malware will be highly effective. Email malware focuses on modeling the propagation dynamics which is a fundamental technique for developing countermeasures to reduce email malware’s spreading speed and prevalence. Modern email malware exhibits two new features, reinjection and self-start. Reinjection is an infected user sends out malware copies whenever this user visits the malicious hyperlinks or attachments. Self-start refers to the behavior that malware starts to spread whenever compromised computers restart or certain files are visited. For address this problem, to derive a novel difference equation based analytical model by introducing a new concept of virtual dirty user. Propose a new analytical model to enhanced OLSR protocol which is a trust based technique to secure the OLSR nodes against the attack. The proposed solution called EOLSR is an enhancement of the basic OLSR routing protocol, which will be able to detect the presence of malicious nodes in the network.
Development And Implementation Of OFDM Transceiver For WLAN ApplicationsIJERA Editor
Multi-Carrier modulation is a technique for data transmission by multiplexing a low bit-rate data streams to modulated carriers into signal Wideband Carrier. Multi-Carrier transmission has a lot of useful properties such as delay-spread tolerance and spectrum efficiency that encourage their use in untethered broadband communication. OFDM is becoming the chosen modulation technique for wireless communications. OFDM is a multi-carrier modulation scheme with densely spaced sub-carriers that has gained a lot of popularity among the broadband community in the last few years. OFDM can provide large data rate with sufficient robustness to radio channel impairments. OFDM works on the principle of Orthogonality. The orthogonality between subcarriers which is at the core of OFDM modulation requires a perfect synchronization. OFDM has properties like high spectral efficiency, Resiliency to RF interference and Lower multi-path distortion. This work is concentrated in implementing both transmitter and receiver using Matlab software and also to verify whether the transmitted data is obtained at the receiver side. As we are using the OFDM technique we will be having bandwidth efficiency when compared to the normal FDM technique.
An Improved Deterministic Energy Efficient Clustering Protocol for Wireless S...IJERA Editor
In recent development, achieving the deployment of nodes, lifetime, fault tolerance, latency, energy efficiency in brief robustness and high reliability have become the prime research goals of wireless sensor network. In recent years many clustering protocols have been suggested on clustering structure based on heterogeneity. We propose improved deterministic energy-efficient clustering protocol for four types of nodes which extend the stability and lifetime of the network in team of first node get dead. Hence, it increases the heterogeneity and energy level of the network. I-DEC performs better than E-SEP, SEP and DEC with more stability and effective messages shows in simulation results.
Special Elements of a Ternary SemiringIJERA Editor
In this paper we study the notion of some special elements such as identity, zero, absorbing, additive
idempotent, idempotent, multiplicatively sub-idempotent, regular, Intra regular, completely regular, g–regular,
invertible and the ternary semirings such as zero sum free ternary semiring, zero ternary semiring, zero divisor
free ternary semiring, ternary semi-integral domain, semi-subtractive ternary semiring, multiplicative
cancellative ternary semiring, Viterbi ternary semiring, regular ternary semiring, completely ternary semiring
and characterize these ternary semirings.
Mathematics Subject Classification : 16Y30, 16Y99.
Image Restitution Using Non-Locally Centralized Sparse Representation ModelIJERA Editor
Sparse representation models uses a linear combination of a few atoms selected from an over-completed
dictionary to code an image patch which have given good results in different image restitution applications. The
reconstruction of the original image is not so accurate using traditional models of sparse representation to solve
degradation problems which are blurring, noisy, and down-sampled. The goal of image restitution is to suppress
the sparse coding noise and to improve the image quality by using the concept of sparse representation. To
obtain a good sparse coding coefficients of the original image we exploit the image non-local self similarity and
then by centralizing the sparse coding coefficients of the observation image to those estimates. This non-locally
centralized sparse representation model outperforms standard sparse representation models in all aspects of
image restitution problems including de-noising, de-blurring, and super-resolution.
Performance of a Wind System: Case Study of Sidi Daoud SiteIJERA Editor
This paper describes recent developments of systems for the conversion of wind energy. It presents a modeling and simulation of wind energy conversion system at the site of Sidi Daoud using the experimental results obtained by the services of the company STEG and Madee. We determined the performance of machines based on site properties and dimensional characteristics of the device.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Survey on Security for Server Using Spontaneous Face DetectionIJERA Editor
In today’s computerized world, cyber crime has increased. The web network of www also increases day by day. So the protection of software and data in our computers has become very important. For this purpose we are developing the “Server Security System” with the help of some technologies such as GPRS, TCP-IP, SMTP, and MIME. In our project we are developing a system such that we get the image of an unauthorized person or user. To do this we are using a webcam. We send a mail to the authorized person's GPRS phone. For this purpose we use a mobile it can be any mobile. In parallel we are changing the password by generating a random string & then Shutting-Down the computer remotely. By using java programming we can create such applications which will help us to stop the cyber crime. It is not visible to new user so that he is unaware from this software so this will definitely helpful to make them fool.
Agent Oriented Patient Scheduling System: A Concurrent Metatem Based ApproachIJERA Editor
The Problem of Patient Scheduling[6] is a major issue in a Medical Healthcare System[4]. In India, Healthcare
is an 80 billion dollar Industry and is growing at an average rate of 17% annually. However, quality healthcare
is still out of reach for many. Each year thousands of fatalities arise simply due to the fact that patient could not
be provided with proper medical facilities at the right time. A software agent may be a member of a Multi-Agent
System[2][5] (MAS) which is collectively performing a range of complex and intelligent tasks. Using
Concurrent Metatem[3], a Multi-Agent Language, we have attempted to model a patient scheduling
system[4][6] that can help hospitals collaborate among them through a Liaison-Agent, in order to provide
patients with the best care possible. Patients should no longer have to be turned down when hospitals are packed
to capacity; instead, they could simply be shifted to another hospital. Hospitals and even doctors are assigned to
patients after an automated process of matching patient needs with doctor expertise and hospital infrastructureleading
to reduced waiting-time while maximizing efficiency and potentially saving lives.
A Systematic Approach to Improve BOC Power Spectrum for GNSSIJERA Editor
An analysis of digital Phase-modulated signals is performed based on frequency spectrum which consists of a continuous and a number of discrete components at multiples of clock frequencies. The analysis shows that these components depend on the pulse shape function of multi-level digital signals to be phase modulated. In this paper, the effect of duty cycle, rise and fall times of these multi-level digital signals, on the frequency spectrum is studied. It is observed that the duty cycle variation of 10% results 30 dB increase in undesired component and the 10% increase in rise & fall times increase the power of undesired component by 12 dB. The theoretical observations of the effects are applied on the Binary Offset Carrier (BOC) modulated signals as a case study, to discuss their effects in Global Navigation Satellite Systems (GNSS).
Fvm Analysis for Thermal and Hydraulic Behaviour of Circular Finned Mpfhs by ...IJERA Editor
In this exploration the influence of using two types of Nano fluids (Ag-water and Al203-water) as a coolant at volumetric concentration is taken (c= 4%) in micro pin fin heat sink with circular fins in addition to the un-finned micro-channel heat sink is deliberated with the help of commercially available computational fluid dynamics software Fluent 14. The evaluation of flow and heat transfer characteristics of MPFHS and cooling fluids has been made under the similar boundary condition; at the range of Reynolds number used is (100-500). The gotten outcomes is exemplified that, Ag-water Nano fluid is gives the minimum pressure drop and slightly maximum heat transfer rate compared to Al203-water Nano fluid. And circular finned heat sink is dissipating more amount of heat compared to un-finned micro-channel heat sink. But it is also gives the maximum pressure drop due to finned area.
Liquid crystal bio-based epoxy coating with enhanced performanceIJERA Editor
Tetrafunctional rosin based epoxy was synthesized and cured with either rosin based hardener or conventional
phenylene diamine to study the feasibility of producing high performance thermosetting polymer from
renewable resource. The chemical structure of the prepared epoxy was confirmed by elemental analysis, FTIR,
1HNMR, UV, total acid number and epoxy equivalent weight. Dynamic mechanical (DMA) and
thermogravimetric (TGA) analyses results indicate that fully biobased epoxy system possesses high glass
transition temperature (Tg), high modulus (G`) and improved thermal stability.
Fighting Accident Using Eye Detection forSmartphonesIJERA Editor
This paper is an attempt to investigate an important problem and approaches of human eye detection, blinking, and tracking. A new system was proposed and implemented using android technology for smartphones. System creatively reduces accidents due to drivers’ fatigue by focusing on treating the driver after fatigue has been detected to achieve decrease in accident likelihood.
Smartphone's have been the important tools in our society for the abundant functions including communication, entertainment and online office etc. as the pivotal devices of mobile computing. Smartphone development has also become more important than before. Android is one of the emerging leading operating systems for smartphones as an open source system platform. Many smartphones have adopted this platform and more smartphones will do so in the future. The proposed system is well-suited for real world driving conditions since it can be non-intrusive by using video cameras to detect changes. Driver operation and vehicle behavior can be implemented by equipping automobiles with the ability to monitoring the response of the driver. This involves periodically requesting the driver to send a response to the system to indicate alertness. The propose system based on eyes closer count & yawning count of the driver. By monitoring the eyes and face, it is believed that the symptoms of driver fatigue can be detected early enough to avoid a car accident and providing the driver with a warning if the driver takes his or her eye off the road.
Comparison Between Structural Analysis of Residential Building (Flat Scheme) ...IJERA Editor
The recent development in methods to analyze the RC frame structure brings us to this study. This paper is
approach to introduce the comparison between structural analysis of Residential building (Flat Scheme)
subjected to gravity with respect to seismic forces ( in zone II and zone III) for different storey heights.
For structural engineers, seismic load should be considered as important aspect that needs to be included in
the building design. However majority of buildings constructed in India are designed for gravity loading only
and poorly detailed to accommodate lateral loads. The purpose of this paper is to investigate the comparison
between structural analysis of residential building subjected to gravity with respect to seismic forces in zone II
and zone III for different storey heights.
The analysis for residential building (G+3) is carried out by using software SAP by seismic coefficient
method. Columns, beams and footing has been drawn. Microsoft office Excel 2007 programs were used for
drafting , and analysis of columns, beams and footing.
This analysis gives better understanding the seismic performance of buildings. The results show that the
building which is designed only for gravity load is found inadequate to resist seismic load in zone II and zone III.
Single Mode Optical Fiber in Rof System Using DWDMIJERA Editor
Performance analysis was carried out to find the effect of crosstalk in a WDM system. Firstly, analysis of BER
was carried out without crosstalk. Then analysis of BER with crosstalk was done. Using equation for crosstalk,
number of channels was plotted using matlab. System parameters were optimized for a particular crosstalk.
Objective of the thesis work
Performance Analysis is carried out to find the effect of crosstalk due to optical cross connect in a DWDM
system considering a WDM based optical cross connect (OXC). An analysis is carried out to find the amount of
crosstalk due to OXC. The bit error rate performance degradation due to crosstalk is evaluated for OXC
parameter and number of wavelengths per fiber. The optimum parameters such as optimum number of channels
and hops are determined.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International conference On Computer Science And technologyanchalsinghdm
ICGCET 2019 | 5th International Conference on Green Computing and Engineering Technologies. The conference will be held on 7th September - 9th September 2019 in Morocco. International Conference On Engineering Technology
The conference aims to promote the work of researchers, scientists, engineers and students from across the world on advancement in electronic and computer systems.
International Journal of Engineering Research and DevelopmentIJERD Editor
Electrical, Electronics and Computer Engineering,
Information Engineering and Technology,
Mechanical, Industrial and Manufacturing Engineering,
Automation and Mechatronics Engineering,
Material and Chemical Engineering,
Civil and Architecture Engineering,
Biotechnology and Bio Engineering,
Environmental Engineering,
Petroleum and Mining Engineering,
Marine and Agriculture engineering,
Aerospace Engineering.
A Study of Pattern Analysis Techniques of Web Usageijbuiiir1
Web mining is the most important application of data mining techniques to extract knowledge from web data including web document, hyperlinks between documents, usage logs of web sites etc. Web mining has been explored to a vast degree and different techniques have been proposed for a huge variety of applications that includes search engine enhancement, optimization of web services, Business Intelligence, B2B and B2C business etc. Most research on web mining has been from a �process-centric� point of view which defined web mining as a sequence of tasks. In this paper, we highlight the significance of studying the evolving nature of the web pattern analysis (WPA). Web usage mining is used to discover interesting user navigation patterns and can be applied to many real-world problems, such as improving web sites/pages. A Web usage mining system performs five major tasks: i) data collection ii) information filtering iii) pattern discovery iv) pattern analysis and visualization techniques, and v) Knowledge Query Mechanism (KQM). Each task is explained in detail and its related technologies are introduced. The web mining research is a converging research area from several research communities, such as database system, information retrieval, information extraction and artificial intelligence. In this paper we implement how web usage mining techniques can be applied for the customization i.e. web visualization
Web is a collection of inter-related files on one or more web servers while web mining means extracting
valuable information from web databases. Web mining is one of the data mining domains where data
mining techniques are used for extracting information from the web servers. The web data includes web
pages, web links, objects on the web and web logs. Web mining is used to understand the customer
behaviour, evaluate a particular website based on the information which is stored in web log files. Web
mining is evaluated by using data mining techniques, namely classification, clustering, and association
rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, Egovernment, E-policies, E-democracy, Electronic business, security, crime investigation and digital library.
Retrieving the required web page from the web efficiently and effectively becomes a challenging task
because web is made up of unstructured data, which delivers the large amount of information and increase
the complexity of dealing information from different web service providers. The collection of information
becomes very hard to find, extract, filter or evaluate the relevant information for the users. In this paper,
we have studied the basic concepts of web mining, classification, processes and issues. In addition to this,
this paper also analyzed the web mining research challenges.
Web is a collection of inter-related files on one or more web servers while web mining means extracting
valuable information from web databases. Web mining is one of the data mining domains where data
mining techniques are used for extracting information from the web servers. The web data includes web
pages, web links, objects on the web and web logs. Web mining is used to understand the customer
behaviour, evaluate a particular website based on the information which is stored in web log files. Web
mining is evaluated by using data mining techniques, namely classification, clustering, and association
rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, Egovernment, E-policies, E-democracy, Electronic business, security, crime investigation and digital library.
Retrieving the required web page from the web efficiently and effectively becomes a challenging task
because web is made up of unstructured data, which delivers the large amount of information and increase
the complexity of dealing information from different web service providers. The collection of information
becomes very hard to find, extract, filter or evaluate the relevant information for the users. In this paper,
we have studied the basic concepts of web mining, classification, processes and issues. In addition to this,
this paper also analyzed the web mining research challenges.
Web is a collection of inter-related files on one or more web servers while web mining means extracting
valuable information from web databases. Web mining is one of the data mining domains where data
mining techniques are used for extracting information from the web servers. The web data includes web
pages, web links, objects on the web and web logs. Web mining is used to understand the customer
behaviour, evaluate a particular website based on the information which is stored in web log files. Web
mining is evaluated by using data mining techniques, namely classification, clustering, and association
rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, Egovernment, E-policies, E-democracy, Electronic business, security, crime investigation and digital library.
Retrieving the required web page from the web efficiently and effectively becomes a challenging task
because web is made up of unstructured data, which delivers the large amount of information and increase
the complexity of dealing information from different web service providers. The collection of information
becomes very hard to find, extract, filter or evaluate the relevant information for the users. In this paper,
we have studied the basic concepts of web mining, classification, processes and issues. In addition to this,
this paper also analyzed the web mining research challenges.
Web is a collection of inter-related files on one or more web servers while web mining means extracting valuable information from web databases. Web mining is one of the data mining domains where data mining techniques are used for extracting information from the web servers. The web data includes web
pages, web links, objects on the web and web logs. Web mining is used to understand the customer behaviour, evaluate a particular website based on the information which is stored in web log files. Web mining is evaluated by using data mining techniques, namely classification, clustering, and association
rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, Egovernment, E-policies, E-democracy, Electronic business, security, crime investigation and digital library. Retrieving the required web page from the web efficiently and effectively becomes a challenging task
because web is made up of unstructured data, which delivers the large amount of information and increase the complexity of dealing information from different web service providers. The collection of information becomes very hard to find, extract, filter or evaluate the relevant information for the users. In this paper,
we have studied the basic concepts of web mining, classification, processes and issues. In addition to this,
this paper also analyzed the web mining research challenges.
Web is a collection of inter-related files on one or more web servers while web mining means extracting
valuable information from web databases. Web mining is one of the data mining domains where data
mining techniques are used for extracting information from the web servers. The web data includes web
pages, web links, objects on the web and web logs. Web mining is used to understand the customer
behaviour, evaluate a particular website based on the information which is stored in web log files. Web
mining is evaluated by using data mining techniques, namely classification, clustering, and association
rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, Egovernment, E-policies, E-democracy, Electronic business, security, crime investigation and digital library.
Retrieving the required web page from the web efficiently and effectively becomes a challenging task
because web is made up of unstructured data, which delivers the large amount of information and increase
the complexity of dealing information from different web service providers. The collection of information
becomes very hard to find, extract, filter or evaluate the relevant information for the users. In this paper,
we have studied the basic concepts of web mining, classification, processes and issues. In addition to this,
this paper also analyzed the web mining research challenges.
Web is a collection of inter-related files on one or more web servers while web mining means extracting valuable information from web databases. Web mining is one of the data mining domains where data mining techniques are used for extracting information from the web servers. The web data includes web
pages, web links, objects on the web and web logs. Web mining is used to understand the customer behaviour, evaluate a particular website based on the information which is stored in web log files. Web mining is evaluated by using data mining techniques, namely classification, clustering, and association
rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, Egovernment, E-policies, E-democracy, Electronic business, security, crime investigation and digital library. Retrieving the required web page from the web efficiently and effectively becomes a challenging task
because web is made up of unstructured data, which delivers the large amount of information and increase the complexity of dealing information from different web service providers. The collection of information becomes very hard to find, extract, filter or evaluate the relevant information for the users. In this paper,
we have studied the basic concepts of web mining, classification, processes and issues. In addition to this,
this paper also analyzed the web mining research challenges.
Web is a collection of inter-related files on one or more web servers while web mining means extracting valuable information from web databases. Web mining is one of the data mining domains where data mining techniques are used for extracting information from the web servers. The web data includes web
pages, web links, objects on the web and web logs. Web mining is used to understand the customer behaviour, evaluate a particular website based on the information which is stored in web log files. Web mining is evaluated by using data mining techniques, namely classification, clustering, and association
rules. It has some beneficial areas or applications such as Electronic commerce, E-learning, Egovernment, E-policies, E-democracy, Electronic business, security, crime investigation and digital library. Retrieving the required web page from the web efficiently and effectively becomes a challenging task
because web is made up of unstructured data, which delivers the large amount of information and increase the complexity of dealing information from different web service providers. The collection of information becomes very hard to find, extract, filter or evaluate the relevant information for the users. In this paper,
we have studied the basic concepts of web mining, classification, processes and issues. In addition to this,
this paper also analyzed the web mining research challenges.
Certain Issues in Web Page Prediction, Classification and Clustering in Data ...IJAEMSJORNAL
Nowadays, data mining which is a part of web mining plays a vital role in various applications such as search engines, health care centers for extracting the individual patient details among huge database, analyzing disease based on basic criteria, education system for analyzing their performance level with other system, social networking, E-Commerce and knowledge management etc., which extract the information based on the user query. The issues are time taken to mine the target content or webpage from the search engines, space complexity and predicting the frequent webpage for the next user based on users’ behaviour.
ANALYTICAL IMPLEMENTATION OF WEB STRUCTURE MINING USING DATA ANALYSIS IN ONLI...IAEME Publication
In today ’s global business, the web has been the most important means of communication. Clients and customers may find their products online, which is a benefit of doing business online. Web mining is the process of using data mining tools to analyse and extract the information from a Web pages and applications autonomously. Many firms use web structure mining to generate suitable predictions and judgments for business growth, productivity, manufacturing techniques, and more utilizing data mining business strategies. In the online booking domain, optimum web data mining analysis of web structure is a crucial component that gives a systematic manner of new application towards real-time data with various levels of implications. Web structure mining emphases on the construction of the web's hyperlinks. Linkage administration that is done correctly can lead to future connections, which can therefore increase the prediction performance of learnt models. A increased interest in Web mining, structural analysis research has expanded, resulting in a new research area that sits at the crossroads of work in the network analysis, hyperlink and the web mining, structural training, and empirical software design techniques, as well as graph mining. Web structure mining is the development of determining structure data from the web. The proposed WSM approach is a system of finding the structure of data stored over the Web. Web structure mining can encourage the clients to recover the significant records by breaking down the connection situated structure of Web content. Web structure mining has been one of the most important resources for information extraction and the knowledge discovery as the amount of data available online has increased.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
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.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
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Web Page Recommendation Using Web Mining Modraj Bhavsar1 Mrs. P. M. Chavan2 1 (Student, Department of Computer Engineering & IT, VJTI, Mumbai-19)
2(Professor, Department of Computer Engineering & IT, VJTI, Mumbai-19) ABSTRACT: On World Wide Web various kind of content are generated in huge amount, so to give relevant result to user web recommendation become important part of web application. On web different kind of web recommendation are made available to user every day that includes Image, Video, Audio, query suggestion and web page. In this paper we are aiming at providing framework for web page recommendation. 1) First we describe the basics of web mining, types of web mining. 2) Details of each web mining technique.3)We propose the architecture for the personalized web page recommendation. Keywords: Web mining, web recommendation, web personalization, and User sequence data.
I. INTRODUCTION
Web page recommendations are becoming very popular, and are shown as links to related web page, related image, or popular pages at websites. When user sends request to web server, session is created for the user. During session when user browses a website the list of page that user visits is stored as a session data. This sequence can be organized and stored as web session S = d1, d2, d3, where di = page ID of the ith visited page. The main aim of the recommendation system is to predict web page or pages from the user current session data and other user data. The key feature of the recommendation system is to learn from historic data of the current user as well as other user. The recommendation system decides the domain of the current user from the user‟s historic data and then predictsthe pages according to the user‟s domain. Another feature of the recommendation system is to predict web page that is not visited in the user‟s current session. To achieve these features numbers of issues are evolved.
In the past few years many researchers devoted their work to overcome these issues. Web access sequence (WAS) in Web usage data can be represented approaches based on tree structure and probabilistic model [1].These approaches learn from the training datasets to build the transition links between Web-pages. By using these approaches, given the current visited Web-page (referred to as a state) and k previously visited pages (the previous k states), the Web-page(s) that will be visited in the next navigation step can be predicted. The performance of these approaches depends on the sizes of training datasets. The bigger the training dataset size is, the higher the prediction accuracy is. However, these approaches make Web-page recommendations solely based on the Web access sequences learnt from the Web usage data. Therefore, the predicted pages are limited within the discovered Web access sequences, i.e., if a user is visiting a Web-page that is not in the discovered Web access sequence, then these approaches cannot offer any recommendations to this user. We refer to this problem as “new-page problem” in this study. Some studies have shown that semantic- enhanced approaches are effective to overcome the new-page problem [2, 3] and have therefore become far more popular. The use of domain knowledge can provide tremendous advantages in Web-page recommender systems [4]. Domain ontology is commonly used to represent the semantics of Web-pages of a website. It has been shown that integrating domain knowledge with Web usage knowledge enhances the performance of recommender systems using ontology-based Web mining techniques [4-6]. Some studies have shown that semantic- enhanced approaches are effective to overcome the new-page problem [2, 3] and have therefore become far more popular. The use of domain knowledge can provide tremendous advantages in Web-page recommender systems [4]. Domain ontology is commonly used to represent the semantics of Web- pages of a website. It has been shown that integrating domain knowledge with Web usage knowledge enhances the performance of recommender systems using ontology-based Web mining techniques [4-6]. Integrating semantic information with Web usage mining achieved higher performance than classic Web usage mining algorithms [5]. However, one of the big challenges that these approaches are facing is the semantic domain knowledge acquisition and representation. How to effectively construct the domain ontology is an ongoing research topic.
This paper presents method to provide better Webpage recommendation based on Web usage data and user‟s domain knowledge. In this user‟s session
RESEARCH ARTICLE OPEN ACCESS
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data is collected. Using this bipartite graph is created. This graph is made up of two sets first set is all user sets and second set is of domain set. The edge is drawn from set1 to set2 if the user belongs to some domain of set2. Also there is another bipartite graph with different set, in this graph first set is all domains supported by the system, and second set is collection of all web pages. In this graph also edge is drawn fromset1 to set2 if the web page belongs to some domain. This paper is structured as follows: Section II briefs the related work. Section III presents the personalized web page recommendation model. VI concludes this paper and highlights some further work.
II. RELATED WORK
Web mining - is the application of data mining techniques to discover patterns from the Web. According to analysis targets, web mining can be divided into three different types, which are
1. Web usage mining
2. Web content mining and
3. Web structure mining.
2.1. Web Usage Mining
Web usage mining is the process of extracting useful information from server logs e.g. use Web usage mining is the process of finding out what users are looking for on the Internet. Some users might be looking at only textual data, whereas some others might be interested in multimedia data. Web Usage Mining is the application of data mining techniques to discover interesting usage patterns from Web data in order to understand and better serve the needs of Web-based applications. Usage data captures the identity or origin of Web users along with their browsing behavior at a Web site. Web usage mining itself can be classified further depending on the kind of usage data considered:
Web Server Data: The user logs are collected by the Web server. Typical data includes IP address, page reference and access time.
Application Server Data: Commercial application servers have significant features to enable e-commerce applications to be built on top of them with little effort. A key feature is the ability to track various kinds of business events and log them in application server logs.
Application Level Data: New kinds of events can be defined in an application, and logging can be turned on for them thus generating histories of these specially defined events. It must be noted, however, that many end applications require a combination of one or more of the techniques applied in the categories above.
2.2. Web structure Mining
Web structure mining is the process of using graph theory to analyze the node and connection structure of a web site. According to the type of web structural data, web structure mining can be divided into two kinds: 1. Extracting patterns from hyperlinks in the web: a hyperlink is a structural component that connects the web page to a different location. 2. Mining the document structure: analysis of the tree-like structure of page structures to describe HTML or XML tag usage.
2.3. Web Content Mining
Web content mining is the mining, extraction and integration of useful data, information and knowledge from Web page content. The heterogeneity and the lack of structure that permits much of the ever-expanding information sources on the World Wide Web, such as hypertext documents, makes automated discovery, organization, and search and indexing tools of the Internet and the World Wide Web such as Lycos, Alta Vista, WebCrawler, ALIWEB, MetaCrawler, and others provide some comfort to users, but they do not generally provide structural information nor categorize, filter, or interpret documents. In recent years these factors have prompted researchers to develop more intelligent tools for information retrieval, such as intelligent web agents, as well as to extend database and data mining techniques to provide a higher level of organization for semi-structured data available on the web. The agent-based approach to web mining involves the development of sophisticated AI systems that can act autonomously or semi-autonomously on behalf of a particular user, to discover and organize web-based information. There are mainly two approaches for web page recommendation.
1) Traditional approach.
2) Semantic based approach.
In tradition approach association rule mining and probabilistic models are commonly used. Models like sequential modeling are effective in the recommendation [2]. Markov models and tree-based structures are goodto show the transition between different web pages in web session[2]. Some surveys [15, 16] have shown that tree-basedalgorithms, particularly Pre-Order Linked WAP-Tree Mining [13], are outstanding in supportingWeb-page recommendation, compared with other sequencemining algorithms.
The semantic basedapproach uses semantic information into Web-page recommendation models. Using ontology of website recommendation system can be improved significantly. For a website domain ontology is useful for classification of the web pages, and this helps to cluster the web pages and searching
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the web pages. Domain ontology can be obtained by manual or automatic construction approaches. Depending on the domain of interest in the system, we can reuse some existing ontologies or build a new ontology, and then integrate it with Web mining. Web logs in a Web personalization system. In this system, ontology is built with the concepts extracted from the documents, so that the documents can be clustered based on the similarity measure of the ontology concepts. Then, usage data is integrated with the ontology in order to produce semantically enhanced navigational patterns. Subsequently, the system can make recommendations, depending on the input patterns semantically matched with the produced navigational patterns. Liang Wei and Song Lei [18] employ ontology to represent a website‟s domain knowledge using the concepts and significant terms extracted from documents. They generate online recommendations by semantically matching and searching for frequent pages discovered from the Web usage mining process. This approach achieves higher precision rates, coverage rates and matching rates. On the other hand, by mapping Web-pages to domain concepts in a particular semantic model, the recommender system can reason what Web-pages are about, and then make more accurate Web-page recommendations [7, 8]. Alternatively, since Web access sequences can be converted into sequences of ontology instances, Web-page recommendation can be made by ontology reasoning [6, 9]. In these studies, the Web usage mining algorithms find the frequent navigation paths in terms of ontology instances rather than normal Web-page sequences. Generally, ontology has helped to organize knowledge bases systematically and allows systems to operate effectively.
III. WEB PAGE RECOMMENDATION SYSTEM ARCHITECTURE
There will be two phases in the whole process – i) offline tasks that includes datapreprocessing and cleaning followed by Pattern mining, ii) online tasks that concern the
Figure 1: System Architecture
3.1 Data Preprocessing
The preprocessing phase is the first component in the architecture. Web server log file, which is the main source of input, generally contains noisy and irrelevant data. Preprocessing phase consists of data cleaning, user‟s identification and session identification tasks. During preprocessing Web server log files are pruned to remove irrelevant requests such as non-responded requests and requests made by software agents such as Web crawlers and search engines. Each Web page is annotated with semantic information during the development of the Website thus showing which ontology class it is an instance of. The cleaned and filtered Web log file is passed to ontology based Web log parser and all the ontology instances represented by theWeb pages are extracted converting the Web log to a sequence of semantic objects. The preprocessing tasks results in aggregate structures such as user transaction file, containing semantic objects where each object is represented as tuple <page, instancei>, where page represents the Web page which contains the object/product, usually an URL address of the page,and instancei is an instance of a class c € C, from provided ontology O, where i is an index for anenumeration of the objects in the sequence, from the Web sequence database being mined.
3.2 Pattern Mining
Following the data pre-treatment step, pattern mining is performed on the derived user access
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sessions. The representative user navigation pattern can be obtained by clustering algorithms. Clustering of user navigation pattern aims to group sessions into clusters based on their common properties. Access sessions that are obtained by the clustering process are actual patterns of Web user activities. User navigation patterns are defined as follows: Definition 1. A user navigation pattern npcaptures an aggregate view of the behavior of a group of users based on their common interests or information needs. As the results of session clustering, NP = {np1, np2,. . . , npk} is used to represent the set of user navigation patterns, in which each npiis a subset of P, the set of Web pages. The process of the clustering takes three steps: are elaborated as follows: (1) Compute the degree of connectivity between Web pages and create an adjacency matrix. (2) Create an undirected graph corresponding to the adjacency matrix. (3) Find connected component in the graph based on graph search algorithm. Step 1: Compute the degree of connectivity between Web pages and create an adjacency matrix. For each pair of pages a and b, we compute W(a, b), which is the degree of connectivity between Web pages. A new measurement is proposed for approximating the degree of connectivity for each pair of Web pages in a session, which are Time Connectivity and Frequency. Step 2: Create an undirected graph corresponding to the adjacency matrix. The graph structure can be used to store the weights as an adjacency matrix M where each entry Mabcontains the value Wabcomputed according to formula in (3). To limit the number of edge in such graph, element of Mabwhose value is less than the threshold value and is small correlated will be thus discarded. In this study, this threshold is named as MinFreq. Step 3: Find connected component in the graph based on graph search algorithm. The graph partitioning algorithms divide a graph into k disjoint partitions, such that the partitions are connected and there are a small number of connections between the partitions.
Graph partitioning algorithm is utilized to search for groups of strongly correlated Web pages by partitioning the graph according to its connected components. Depth-first search (DFS) is an algorithm for traversing or searching a graph. Starting from a vertex a, DFS induced by M is applied to search for the connected component reachable from this vertex. Once the component has been found, the algorithm checks if there are any nodes that are not considered in the visit. If so, it means that a previously connected component has been split, and therefore, it needs to be identified. To do this, DFS is applied again by starting from one of the nodes that is not yet visited. In the worst case, when all the URLs are in the same cluster, the cost of this algorithmwill be linear in terms of the number of edges in the complete graph G. Two main parameters must be accounted for while the algorithm is applied to the undirected graph. Minimum frequency and minimum cluster size are two parameters that significantly affect mining of navigation patterns. MinFreq is a minimum frequency parameter for filtering weights that are below a constant value. The edges of the graph whose values are less than MinFreq are inadequately correlated and are thus not considered by the DFS graph search algorithm. DFS also considers all the connected components that possess the number of nodes greater than a fixed size. Otherwise the rest of components will be considered as insignificant. In this paper, the minimum cluster size is termed as MinClusterSize. In this study, connected components that have been created based on graph partitioning algorithm are considered as a set of navigation patterns. At the end of this step, the algorithm shows NP = {np1, np2,. . . , npk}, whereby NP is a set of navigation patterns. NP can also be considered as a set of clusters that will further be utilized during the online phase. The algorithm for navigation pattern mining (clustering) based on graph partitioning algorithm is shown below. Input:
Cleaned, filtered, and sessionized Log file.
MinFreq.
MinClusterSize.
Output:
List of Clusters C
L[p] = P; //Assign all URL‟s to a list of web //pages foreach (Pi, Pj) € L[ p ] do //for all pair of //web pages M (i, j) = WeightFormula (Pi, Pj); //computing the weight based on formula (3) Edge (i, j) = M (i, j) ; end for //There is an undirected graph (E, V) forall Edge (u, v) € Graph (E, V) do //removing all edges that its weight is below //than MinFreq ifEdge (u, v) <MinFreqthen remove (Edge(u, v)) ; end if end for forall vertices (u) € Graph (E, V) do Cluster [i] = DFS (u) ;//doing the DFS //algorithm ifcluster[i] <MinClusterSize//remove the //cluster that its size is below than //MinClusterSize remove (Cluster[i]);
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end if i = i+1 end for return (Cluster) ;
3.3 Online Recommendation Phase
The aim of a recommender system is to determine which Web pages are more likely to be accessed by the user in the future. In this phase active user‟s navigation history is compared with the discovered Sequential Association rules in order to recommend a new page or pages to the user in real time. Generally not all the items in the active session path are taken into account while making a recommendation. A very earlier page that the user visited is less likely to affect the next page since users generally make the decision about what to click by the most recent pages. Therefore the concept of window count is introduced. Window count parameter „n’ defines the maximum number of previous page visits to be used while recommending a new page. Since the association rules are in the form of ontology individuals, the user‟s navigational history is converted into the sequence of ontology instances. Then the semantic rich association rules and user navigation history are joined in order to produce recommendations. In the recommendation phase, in the first instance, the most recently navigated item is taken as the search pattern. All the semantic–rich association rules are scanned and the association rules whose antecedent part is equal to the search pattern are added to the recommendation set. This step iterates window count times and at each iteration, the search pattern is extended by one item. The recommendation set constitutes the set of semantic rich association rules sorted in the decreasing order of their confidence. After constructing the recommendation set, the page recommendation commences. Semantic distance between objects is taken into consideration to solve the ambiguity problem. For instance consider the following two semantic rich association rules and AB ---> C AB--- >D where A, B, C, D are semantic objects. If semantic distance (B,D) < semantic distance(B,C) meaning that D is semantically closer to B than C is, then recommendation engine will prefer D over C and the page(s) representing product D will be recommended. Such capability is not provided by regular association rules. The consequent part of the rule contains ontology individuals; therefore the instances should be converted to the real Web objects. The Web pages for the Web objects present in the recommendation set are recommended.
IV. FUTURE WORK
There are a number of aspects that merit further improvement by the system. We can take into account the semantic knowledge about underlying domain to improve the quality of the recommendations. Integrating semantic Web and Web usage mining can help in achieving best recommendations from the dynamic and huge Web sites. The recommendations will be much more relevant, since they will be some relation to each other; instead of just following the navigation patterns.
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