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.
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.
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 Page Recommendation Using Web MiningIJERA Editor
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.
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.
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 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.
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.
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 Page Recommendation Using Web MiningIJERA Editor
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.
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.
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 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.
A NEW IMPROVED WEIGHTED ASSOCIATION RULE MINING WITH DYNAMIC PROGRAMMING APPR...cscpconf
With the rapid development of Internet, Web search has been taken an important role in our
ordinary life. In web search, mining frequent patterns in large database is a major research area. Due to increase of user activities on web, web-searching methods, to predict the nextrequest of user visits in web pages plays a major role. Web searching methods are helpful to provide quality results, timely answer and also offer a customized navigation. In web search, Association rule mining is an important data analysis method to discover associated web pages. Most of the researchers implemented association mining using Apriori algorithm with binary representation. The problem of this approach is not address the issue like the navigation order of web pages. To overcome this problem researchers proposed a weighted Apriori to maintain navigation order but unable to produce optimal results. With the goal of a most favorable result we proposed a novel approach which combines weighted Apriori and dynamic programming. The experimental result shows that this approach maintains the navigation order of web pages and achieves a best solution. The proposed technique enhances the web site effectiveness, increases the user browsing knowledge, improves the prediction accuracy and decreases the computational complexities.
Integrated Web Recommendation Model with Improved Weighted Association Rule M...ijdkp
World Wide Web plays a significant role in human life. It requires a technological improvement to satisfy
the user needs. Web log data is essential for improving the performance of the web. It contains large,
heterogeneous and diverse data. Analyzing g the web log data is a tedious process for Web developers,
Web designers, technologists and end users. In this work, a new weighted association mining algorithm is
developed to identify the best association rules that are useful for web site restructuring and
recommendation that reduces false visit and improve users’ navigation behavior. The algorithm finds the
frequent item set from a large uncertain database. Frequent scanning of database in each time is the
problem with the existing algorithms which leads to complex output set and time consuming process. The
proposed algorithm scans the database only once at the beginning of the process and the generated
frequent item sets, which are stored into the database. The evaluation parameters such as support,
confidence, lift and number of rules are considered to analyze the performance of proposed algorithm and
traditional association mining algorithm. The new algorithm produced best result that helps the developer
to restructure their website in a way to meet the requirements of the end user within short time span.
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.
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.
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.
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
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 Web Page Recommendation and Data PreprocessingIJCERT
In today’s era, as we all know internet technologies are growing rapidly. Along with this, instantly, Web page recommendations are also improving. The aim of a Web page recommender system is to predict the Web page or pages, which will be visited from a given Web-page of a website. Data preprocessing is one basic and essential part of Web page recommendation. Data preprocessing consists of cleanup and constructing data to organize for extracting pattern. In this paper, we discuss and focus on Web page Recommendation and role of data preprocessing in Web page recommendation, considering how data preprocessing is related to Web page recommendation.
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.
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.
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.
A NEW IMPROVED WEIGHTED ASSOCIATION RULE MINING WITH DYNAMIC PROGRAMMING APPR...cscpconf
With the rapid development of Internet, Web search has been taken an important role in our
ordinary life. In web search, mining frequent patterns in large database is a major research area. Due to increase of user activities on web, web-searching methods, to predict the nextrequest of user visits in web pages plays a major role. Web searching methods are helpful to provide quality results, timely answer and also offer a customized navigation. In web search, Association rule mining is an important data analysis method to discover associated web pages. Most of the researchers implemented association mining using Apriori algorithm with binary representation. The problem of this approach is not address the issue like the navigation order of web pages. To overcome this problem researchers proposed a weighted Apriori to maintain navigation order but unable to produce optimal results. With the goal of a most favorable result we proposed a novel approach which combines weighted Apriori and dynamic programming. The experimental result shows that this approach maintains the navigation order of web pages and achieves a best solution. The proposed technique enhances the web site effectiveness, increases the user browsing knowledge, improves the prediction accuracy and decreases the computational complexities.
Integrated Web Recommendation Model with Improved Weighted Association Rule M...ijdkp
World Wide Web plays a significant role in human life. It requires a technological improvement to satisfy
the user needs. Web log data is essential for improving the performance of the web. It contains large,
heterogeneous and diverse data. Analyzing g the web log data is a tedious process for Web developers,
Web designers, technologists and end users. In this work, a new weighted association mining algorithm is
developed to identify the best association rules that are useful for web site restructuring and
recommendation that reduces false visit and improve users’ navigation behavior. The algorithm finds the
frequent item set from a large uncertain database. Frequent scanning of database in each time is the
problem with the existing algorithms which leads to complex output set and time consuming process. The
proposed algorithm scans the database only once at the beginning of the process and the generated
frequent item sets, which are stored into the database. The evaluation parameters such as support,
confidence, lift and number of rules are considered to analyze the performance of proposed algorithm and
traditional association mining algorithm. The new algorithm produced best result that helps the developer
to restructure their website in a way to meet the requirements of the end user within short time span.
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.
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.
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.
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
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 Web Page Recommendation and Data PreprocessingIJCERT
In today’s era, as we all know internet technologies are growing rapidly. Along with this, instantly, Web page recommendations are also improving. The aim of a Web page recommender system is to predict the Web page or pages, which will be visited from a given Web-page of a website. Data preprocessing is one basic and essential part of Web page recommendation. Data preprocessing consists of cleanup and constructing data to organize for extracting pattern. In this paper, we discuss and focus on Web page Recommendation and role of data preprocessing in Web page recommendation, considering how data preprocessing is related to Web page recommendation.
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.
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.
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.
MULTIFACTOR NAÏVE BAYES CLASSIFICATION FOR THE SLOW LEARNER PREDICTION OVER M...ijcsa
The high school students must be observed for their slow learning or quick learning abilities to provide
them with the best education practices. Such analysis can be perfectly performed over the student
performance data. The high school student data has been obtained from the schools from the various
regions in Punjab, a pivotal state of India. The complete student data and the selective data of almost 1300
students obtained from one school in the regions has been undergone the test using the proposed model in
this paper. The proposed model is based upon the naïve bayes classification model for the data
classification using the multi-factor features obtained from the input dataset. The subject groups have been
divided into the two primary groups: difficult and normal. The classification algorithm has been applied
individually over data grouped in the various subject groups. Both of the early stage classification events
have produced the almost similar results, whereas the results obtained from the classification events over
the averaging factors and the floating factors told the different story than the early stage classification. The
proposed model results have shown that the deep analysis of the data tells the in-depth facts from the input
data. The proposed model can be considered as the effective classification model when evaluated from the
results described in the earlier sections.
MULTIFACTOR NAÏVE BAYES CLASSIFICATION FOR THE SLOW LEARNER PREDICTION OVER M...ijcsa
The high school students must be observed for their slow learning or quick learning abilities to provide
them with the best education practices. Such analysis can be perfectly performed over the student
performance data. The high school student data has been obtained from the schools from the various
regions in Punjab, a pivotal state of India. The complete student data and the selective data of almost 1300
students obtained from one school in the regions has been undergone the test using the proposed model in
this paper. The proposed model is based upon the naïve bayes classification model for the data
classification using the multi-factor features obtained from the input dataset. The subject groups have been
divided into the two primary groups: difficult and normal. The classification algorithm has been applied
individually over data grouped in the various subject groups. Both of the early stage classification events
have produced the almost similar results, whereas the results obtained from the classification events over
the averaging factors and the floating factors told the different story than the early stage classification. The
proposed model results have shown that the deep analysis of the data tells the in-depth facts from the input
data. The proposed model can be considered as the effectiv
Semantically enriched web usage mining for predicting user future movementsIJwest
Explosive and quick growth of the World Wide Web has resulted in intricate Web sites, demanding
enhanced user skills and sophisticated tools to help the Web user to find the desi
red information. Finding
desired information on the Web has become a critical ingredient of everyday personal, educational, and
business life. Thus, there is a demand for more sophisticated tools to help the user to navigate a Web site
and find the desired
information. The users must be provided with information and services specific to
their needs, rather than an undiffere
ntiated mass of information.
For discovering interesting and frequent
navigation patterns from Web server logs many Web usage mining te
chniques have been applied. The
recommendation accuracy of solely usage based techniques can be improved by integrating Web site
content and site structure in the personalization process.
Herein, we propose Semantically enriched Web Usage Mining method (S
WUM), which combines the fields
of Web Usage Mining and Semantic Web. In the proposed method, the undirected graph derived from
usage data is enriched with rich semantic information extracted from the Web pages and the Web site
structure. The experimental
results show that the SWUM generates accurate recommendations with
integration of usage, semantic data and Web site structure. The results shows that proposed method is able
to achieve 10
-
20%
better accuracy than the solely usage based model, and 5
-
8% bet
ter than an ontology
based model.
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.
Web personalization using clustering of web usage dataijfcstjournal
The exponential growth in the number and the complexity of information resources and services on the Web
has made log data an indispensable resource to characterize the users for Web-based environment. It
creates information of related web data in the form of hierarchy structure through approximation. This
hierarchy structure can be used as the input for a variety of data mining tasks such as clustering,
association rule mining, sequence mining etc.
In this paper, we present an approach for personalizing web user environment dynamically when he
interacting with web by clustering of web usage data using concept hierarchy. The system is inferred from
the web server’s access logs by means of data and web usage mining techniques to extract the information
about users. The extracted knowledge is used for the purpose of offering a personalized view of the
services to users.
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
Similar to WEB MINING – A CATALYST FOR E-BUSINESS (20)
Advanced Computing: An International Journal (ACIJ) is a peer-reviewed, open access peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced computing. The journal focuses on all technical and practical aspects of high performance computing, green computing, pervasive computing, cloud computing etc. The goal of this journal is to bring together researchers and a practitioners from academia and industry to focus on understanding advances in computing and establishing new collaborations 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 computing.
Call for Papers - Advanced Computing An International Journal (ACIJ) (2).pdfacijjournal
Submit your Research Papers!!!
Advanced Computing: An International Journal ( ACIJ )
ISSN: 2229 -6727 [Online] ; 2229 - 726X [Print]
Webpage URL: http://airccse.org/journal/acij/acij.html
Submission URL: http://coneco2009.com/submissions/imagination/home.html
Submission Deadline : April 08, 2023
Here's where you can reach us : acijjournal@yahoo.com or acij@aircconline
Advanced Computing: An International Journal (ACIJ
)
is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the advancedcomputing. The journal focuses on all technical and practical aspects of high performancecomputing, green computing, pervasive computing, cloud computing etc. The goal of this journalis to bring together researchers anda practitioners from academia and industry to focus onunderstanding advances in computing and establishing new collaborations in these areas
Submit your Research Papers!!!
Advanced Computing: An International Journal ( ACIJ )
ISSN: 2229 -6727 [Online] ; 2229 - 726X [Print]
Webpage URL: http://airccse.org/journal/acij/acij.html
Submission URL: http://coneco2009.com/submissions/imagination/home.html
Here's where you can reach us : acijjournal@yahoo.com or acij@aircconline.com
7thInternational Conference on Data Mining & Knowledge Management (DaKM 2022)acijjournal
7thInternational Conference on Data Mining & Knowledge Management (DaKM 2022)provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum.
7thInternational Conference on Data Mining & Knowledge Management (DaKM 2022)acijjournal
7thInternational Conference on Data Mining & Knowledge Management (DaKM 2022)provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum.
7thInternational Conference on Data Mining & Knowledge Management (DaKM 2022)acijjournal
7thInternational Conference on Data Mining & Knowledge Management (DaKM 2022)provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum.
4thInternational Conference on Machine Learning & Applications (CMLA 2022)acijjournal
4thInternational Conference on Machine Learning & Applications (CMLA 2022)will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
7thInternational Conference on Data Mining & Knowledge Management (DaKM 2022)acijjournal
7thInternational Conference on Data Mining & Knowledge Management (DaKM 2022)provides a forum for researchers who address this issue and to present their work in a peer-reviewed forum.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 the following areas, but are not limited to these topics only.
3rdInternational Conference on Natural Language Processingand Applications (N...acijjournal
3rdInternational Conference on Natural Language Processing and Applications (NLPA 2022)will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Natural Language Computing and its applications. The Conference looks for significant contributions to all major fieldsof the Natural Language processing in theoretical and practical aspects.
4thInternational Conference on Machine Learning & Applications (CMLA 2022)acijjournal
4thInternational Conference on Machine Learning & Applications (CMLA 2022)will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of on Machine Learning & Applications. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
Graduate School Cyber Portfolio: The Innovative Menu For Sustainable Developmentacijjournal
In today’s milieu, new demands and trends emerge in the field of Education giving teachers of Higher Education Institutions (HEI’s) no choice but to be innovative to cope with the fast changing technology. To be naturally innovative, a graduate school teacher needs to be technologically and pedagogically competent. One of the ways to be on this level is by creating his cyber portfolio to support students’ eportfolio for lifelong learning. Cyber portfolio is an innovative menu for teachers who seek out strategies to integrate technology in their lessons. This paper presents a straightforward preparation on how to innovate a cyber portfolio that has its practical and breakthrough solution against expensive and inflexible vended software which often saddle many universities. Additionally, this cyber portfolio is free and it addresses the 21st century skills of graduate students blended with higher order thinking skills, multiple intelligence, technology and multimedia.
Genetic Algorithms and Programming - An Evolutionary Methodologyacijjournal
Genetic programming (GP) is an automated method for creating a working computer program from a high-level problem statement of a problem. Genetic programming starts from a high-level statement of “what needs to be done” and automatically creates a computer program to solve the problem. In artificial intelligence, genetic programming (GP) is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user defined task. It is a specialization of genetic algorithms (GA) where each individual is a computer program. It is a machine learning technique used to optimize a population of computer programs according to a fitness span determined by a program's ability to perform a given computational task. This paper presents a idea of the various principles of genetic programming which includes, relative effectiveness of mutation, crossover, breeding computer programs and fitness test in genetic programming. The literature of traditional genetic algorithms contains related studies, but through GP, it saves time by freeing the human from having to design complex algorithms. Not only designing the algorithms but creating ones that give optimal solutions than traditional counterparts in noteworthy ways.
Data Transformation Technique for Protecting Private Information in Privacy P...acijjournal
Data mining is the process of extracting patterns from data. Data mining is seen as an increasingly important tool by modern business to transform data into an informational advantage. Data
Mining can be utilized in any organization that needs to find patterns or relationships in their data. A group of techniques that find relationships that have not previously been discovered. In many situations, the extracted patterns are highly private and it should not be disclosed. In order to maintain the secrecy of data,
there is in need of several techniques and algorithms for modifying the original data in order to limit the extraction of confidential patterns. There have been two types of privacy in data mining. The first type of privacy is that the data is altered so that the mining result will preserve certain privacy. The second type of privacy is that the data is manipulated so that the mining result is not affected or minimally affected. The aim of privacy preserving data mining researchers is to develop data mining techniques that could be
applied on data bases without violating the privacy of individuals. Many techniques for privacy preserving data mining have come up over the last decade. Some of them are statistical, cryptographic, randomization methods, k-anonymity model, l-diversity and etc. In this work, we propose a new perturbative masking technique known as data transformation technique can be used for protecting the sensitive information. An
experimental result shows that the proposed technique gives the better result compared with the existing technique.
Advanced Computing: An International Journal (ACIJ) acijjournal
Advanced Computing: An International Journal (ACIJ) is a bi monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the advanced computing. The journal focuses on all technical and practical aspects of high performance computing, green computing, pervasive computing, cloud computing etc. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding advances in computing and establishing new collaborations in these areas.
E-Maintenance: Impact Over Industrial Processes, Its Dimensions & Principlesacijjournal
During the course of the industrial 4.0 era, companies have been exponentially developed and have
digitized almost the whole business system to stick to their performance targets and to keep or to even
enlarge their market share. Maintenance function has obviously followed the trend as it’s considered one
of the most important processes in every enterprise as it impacts a group of the most critical performance
indicators such as: cost, reliability, availability, safety and productivity. E-maintenance emerged in early
2000 and now is a common term in maintenance literature representing the digitalized side of maintenance
whereby assets are monitored and controlled over the internet. According to literature, e-maintenance has
a remarkable impact on maintenance KPIs and aims at ambitious objectives like zero-downtime.
10th International Conference on Software Engineering and Applications (SEAPP...acijjournal
10th International Conference on Software Engineering and Applications (SEAPP 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Software Engineering and Applications. The goal of this Conference is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts and establishing new collaborations in these areas.
10th International conference on Parallel, Distributed Computing and Applicat...acijjournal
10th International conference on Parallel, Distributed Computing and Applications (IPDCA 2021) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Parallel, Distributed Computing. Original papers are invited on Algorithms and Applications, computer Networks, Cyber trust and security, Wireless networks and mobile Computing and Bioinformatics. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
DETECTION OF FORGERY AND FABRICATION IN PASSPORTS AND VISAS USING CRYPTOGRAPH...acijjournal
In this paper, we present a novel solution to detect forgery and fabrication in passports and visas using
cryptography and QR codes. The solution requires that the passport and visa issuing authorities obtain a
cryptographic key pair and publish their public key on their website. Further they are required to encrypt
the passport or visa information with their private key, encode the ciphertext in a QR code and print it on
the passport or visa they issue to the applicant.
The issuing authorities are also required to create a mobile or desktop QR code scanning app and place it
for download on their website or Google Play Store and iPhone App Store. Any individual or immigration
authority that needs to check the passport or visa for forgery and fabrication can scan its QR code, which
will decrypt the ciphertext encoded in the QR code using the public key stored in the app memory and
displays the passport or visa information on the app screen. The details on the app screen can be
compared with the actual details printed on the passport or visa. Any mismatch between the two is a clear
indication of forgery or fabrication.
Discussed the need for a universal desktop and mobile app that can be used by immigration authorities and
consulates all over the world to enable fast checking of passports and visas at ports of entry for forgery
and fabrication.
Detection of Forgery and Fabrication in Passports and Visas Using Cryptograph...acijjournal
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The issuing authorities are also required to create a mobile or desktop QR code scanning app and place it for download on their website or Google Play Store and iPhone App Store. Any individual or immigration authority that needs to check the passport or visa for forgery and fabrication can scan its QR code, which will decrypt the ciphertext encoded in the QR code using the public key stored in the app memory and displays the passport or visa information on the app screen. The details on the app screen can be compared with the actual details printed on the passport or visa. Any mismatch between the two is a clear indication of forgery or fabrication.
Discussed the need for a universal desktop and mobile app that can be used by immigration authorities and consulates all over the world to enable fast checking of passports and visas at ports of entry for forgery and fabrication.
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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.
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/
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1. Advanced Computing: An International Journal ( ACIJ ), Vol.3, No.6, November 2012
DOI : 10.5121/acij.2012.3602 9
WEB MINING – A CATALYST FOR E-BUSINESS
Abdul Rahaman Wahab Sait1
and Dr.T.Meyappan2
1
Department of Computer Science, Shaqra University, Alquwaya,
Kingdom of Saudi Arabia
rahamaan@gmail.com
2
Department of Computer Science and Engineering, Alagappa University, Karaikudi,
Tamilnadu, India
meyslotus@yahoo.com
ABSTRACT
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.
KEYWORDS
E-Business, Web Usage Mining, Web Content Mining, World Wide Web & Pattern Extraction
1. INTRODUCTION
Web mining is the subset of data mining, which works with the extraction of interesting
knowledge from the WWW. Internet is a back bone for E-Business. It is a medium for the
vendor to reach the customer and serve them in a better way to make them to revisit their site.
Satisfying one customer gives more customers to the particular vendor. Data mining is the
knowledge discovery technique from the huge amount of data. To mine the interesting user
pattern from the huge pool of data, we can employ the web mining to improve the better
understanding of the customer behaviour. This area of research is so huge today partly due to
the interests of various research communities, the tremendous growth of information sources
available on the web and recent interest in E-Business. Web mining field consists of main three
categories, web usage mining, web structure mining and web content mining. In web usage
mining the goal is to examine web page usage patterns in order to learn about a web system’s
users or the relationships between the documents. Web usage mining is useful for providing
personalized web services, an area of web mining research that has lately become active. It
promises to help tailor web services, such as web search engines to the preferences of each
individual user [5].
E-Business is the electronic version of business which relies on internet. Today selling and
buying are happening in web, even services also been done through internet. In fig 1 we gave
the pictorial representation of E-Business. Enterprise resource planning online software is there
to do outsourcing work. To attract the customers it is very important for the web site owner to
provide the information in a different way from the other website. To do that work web mining
can be taken as a tool to know the users and web behaviour.
2. Advanced Computing: An International Journal ( ACIJ ), Vol.3, No.6, November 2012
10
Figure 1 – A Typical E-Business
As on Dec 2011, 135,676,044 [10] domains have been active in the web. It shows the important
of the pattern extraction, which has taken from the web logs to improve the way of providing
information to increase the number of customers. For example, if a company is having a website
for service purpose or product selling purpose then they should know the customer behavior
form the pattern or clustering.
2. RELATED WORK
S.K. Pani et al., presented an overview of web usage mining and also provided a survey of the
pattern extraction algorithm used for web usage mining [1].
R.Cooley et al., presents an information about web usage mining and web content mining. They
have studied different types of tools which are useful for pattern discovery. They proposed an
overview on web content mining [2].
Chia – Hui Chang et al., proposed a pattern discovery approach to the rapid generation of
information extractors that can extract structured data from semi – structured web documents.
They have introduced a system for information extraction based on pattern discovery [3].
Rajni pamnani and Pramila chawan provided a survey and analysis of web usage mining
systems and technologies. They also discussed about an application of an online recommender
system that dynamically generates links to pages that have not yet been visited by a user [11].
Shohreh Ajoudanian and Mohammad Davarpanah Jazi proposed a method which new data
mining algorithm that increases the speed of information matching. They have presented a
mining algorithm that matches correlated attributes with smaller cost.Maintaining the Integrity
of the Specifications [4].
3. WEB USAGE MINING
It is a process of extracting meaningful pattern from the web. In this section we are going to
explain the mechanism of web usage mining. Data is very important, without data mining
process will not begin. The sources of data are server access logs, referrer logs, agent logs and
client side cookies. Client side cookies are not important source of data because those data
stored in the client side [1][2][3], so it is fully depend upon the user or customer. They may
delete the cookies after surfing the net.
Web server will take the entire request from the user and transfer it to the server. All the logging
data will be found in web server log file. This file contains the entire request made to the web
server, stored in a chronological order. A common log file format is the way to store the entire
request made by the user.
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Web usage mining studies reported to date have mined for association rules, temporal
sequences, clusters and path expressions. As the approach in which the web is used continues to
expand, there is a continual need to figure out new kinds of knowledge about user behavior that
needs to mined [6][11].
4. PATTERN EXTRACTION METHOD
Fig 2 shows the steps in pattern extraction. Those steps are the common method for the
extraction of the pattern from the log files. They are
4.1. Data Collection
In section 3, we have explained the data collection and sources of data. Data collection on the
WWW is incremental and also scattered in its very nature. Hence there is a need to develop
mining algorithms that take as input the existing data, mined knowledge and the new data and
develop a new model in an efficient manner.
If all the data were to be integrated before mining, a lot of valuable information could be
extracted. However, an approach of collecting data from all possible server logs is non –
scalable and impractical. Hence there needs to be an approach where knowledge mined from
various logs can be integrated together into a more ample model [1][3].
Figure 2 – Method of Pattern Extraction
4.2. Data Pre-processing
Web data are semi – structured. It contains mixture of much kind of data, so it is very noisy. It is
necessary to give pre-treatment to carry on a unification transformation to those databases.
Unwanted data like log image entries and robot assesses can be cleaned at this stage. Robot
assess is nothing but a programmed access of information without using a human interaction.
4.3. Pattern Extraction
Extraction of pattern from the pre processed data can be done by using three categories. The
three categories are Association rule mining, Clustering and Classification. Applying any one of
the category we will get the pattern from the web log. Today we have lots of free web mining
software and open source. Here it is not that much important to stress which category is best for
the extraction.
4.4. Pattern Analysis
After the pattern extraction, there is a need to develop techniques and tools for enabling the
analysis of discovered patterns. These techniques are expected to draw from a number of fields
including statistics, graphics and visualization, usability analysis and database querying.
Analyzing the pattern is very important to deploy the pattern in the site.
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5. WEB CONTENT MINING
It is the process of information discovery from sources across the WWW. It is a form of text
mining and can take advantage of the semi – structured nature of web page text [4][5].To mine
information from deep web that is a large set of dynamic queryable databases, we need a system
that can extract automatically. For this purpose we use web content mining techniques and can
take advantage of the semi – structured nature of web page text.
5.1. Agent Based Approach
The agent approach uses so called web agents to collect relevant information from the www. A
web agent is a program that visits a web site and filters the information the user is interested in.
There are three subtypes for the agent based approach: Intelligent search agents, information
filtering / categorization and the personalized web agents.
Figure 3 – Classification of Web Content Mining
5.2. Database Approach
The database approach for web mining tries to develop techniques for organizing semi –
structured data stored in the web into more structured collections of information resources.
Standard database querying mechanisms and data mining techniques can be used to analyze
those collections. The database approach further classified into two types multilevel database
and web query systems.
6. WEB MINING – AS A CATALYST
Web mining makes use of software agent to activate targeted offers as occurrence take place in
real time. An agent is a collection of program that gains access on behalf of a process. It
provides an enterprise the integrated tools to investigate all type of data resource from several
departments from different position from different arrangements for a collection of deliverables
such as tendency to procure scores and prediction of customer behavior. In the previous sections
we have explained the methods involved in web usage mining and web content mining. It is
necessary to know how these concepts can be employed to improve the business in the web. The
fig. 4 shows the utilization of web mining as a catalyst for e-business.
Figure 4 – Web mining – as a Catalyst
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The above figure shows the pictorial view of the web mining process to help the e – business.
Software agents are exist to extract the information from the web data, using those software it is
easy to know competitor web information. After drawing a clear picture of the competitor
information, we can improve our website structure and presentation of information. This results
more number of users to the website. To promote e-business, we need a best recipe to provide
information in an attractive way. Today lot of businesses are happening on the web. Customers
are very important for the vendor to survive in the business world. Many portals are there in the
web for selling and buying the product. Everyone has to do something special to cover a group
of people to bring more number of people to their business [7][8].
The two steps are in the process as follows:
1. Extracting the patterns from the competitors’ site through web mining software agents.
2. Implementing the new changes in the website.
Using the web mining technique the organizations can enhance their own website in a better
way. User behaviour is the important thing to know the stage of the business. By using pattern
extraction method of web usage mining the website owner can know the user’s behavior. To
know the competitor position is also an important one to do a better enhancement of website, to
do that web content mining technique exist. By using that the website owner can know the
competitors site information.
Analyzing data from web logs can help organizations determine the life time value of
customers, cross marketing strategies across products and effectiveness of promotional
campaigns among other things. It can also provide information on how to restructure a website
to create a more effective organizational presence and shed light on more effective management
of workgroup communication and organizational infrastructure. For selling advertisements on
the WWW, analyzing user access patterns helps in targeting advertisements to specific group of
users. More sophisticated systems and techniques for discovery and analysis of patterns are now
emerging in the market [1][9].
7. CONCLUSIONS
There is a budding trend among companies, organizations and individuals alike to gather
information through web mining to utilize that information in their best interest. It is a
demanding job for them to fulfill the user needs and keep their concentration in their website.
This paper gave an idea about web mining and how it can be utilized in an efficient way to
improve the business. Customer behavior is very important for an organization to enhance the
way of providing information to attract them. Analysis of significant information will be helpful
for organization to develop promotions that are more effective, internet accessibility, inter –
company communication, structure and productive marketing skills through web usage mining.
Pattern extraction and web content mining are the best tools to know the customer and web
behavior.
REFERENCES
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Authors
1. ABDUL RAHAMAN WAHAB SAIT was born in Apr. 19, 1981 and he
has completed his Masters in Information technology in 2003 in Madras
University, India. Later he has done his Master of philosophy in computer
science in 2007 at Periyar university, India. Now he is working as a Lecturer
in Computer science, Alquwaya, Shaqra University,Kingdom of Saudi
Arabia. He got interest in Virtual reality and Artificial Neural Networks. He
has written many computer articles and presented paper in National
conference in India
2. Dr. T.Meyyappan M.Sc,M.Phil,M.B.A currently, Associate Professor,
Department of ComputerScience and Engineering, Alagappa University,
Karaikudi, TamilNadu. He has published a number of research papers in
National and International journals and conferences. He has developed
Software packages for Examination, Admission Processing and official
Website of Alagappa University. As a Co-Investigator, he has completed
1.70 crore project on smart and secure environment funded by NTRO, New
Delhi. He has been honoured with Best Citizens of India Award 2012. His
research areas include Operational Research, Digital Image Processing, Fault
Tolerant computing, Network security and Data Mining.