Mining for Web Personalization

Web Mining ◽  
2011 ◽  
pp. 27-49 ◽  
Author(s):  
Penelope Markellou ◽  
Maria Rigou ◽  
Spiros Sirmakessis
Keyword(s):  
Web Mining ◽  
Information Overload ◽  
Close Relation ◽  
Access To Information ◽  
Web Personalization ◽  
Current Trends ◽  
Technical Issues ◽  
Human Capability ◽  
Scientific Results ◽  
The Web

The Web has become a huge repository of information and keeps growing exponentially under no editorial control, while the human capability to find, read and understand content remains constant. Providing people with access to information is not the problem; the problem is that people with varying needs and preferences navigate through large Web structures, missing the goal of their inquiry. Web personalization is one of the most promising approaches for alleviating this information overload, providing tailored Web experiences. This chapter explores the different faces of personalization, traces back its roots and follows its progress. It describes the modules typically comprising a personalization process, demonstrates its close relation to Web mining, depicts the technical issues that arise, recommends solutions when possible, and discusses the effectiveness of personalization and the related concerns. Moreover, the chapter illustrates current trends in the field suggesting directions that may lead to new scientific results.

Mining for Web Personalization

2011 ◽  
pp. 77-97
Author(s):  
Penelope Markellou ◽  
Maria Rigou ◽  
Spiros Sirmakessis
Keyword(s):  
Web Mining ◽  
Information Overload ◽  
Close Relation ◽  
Access To Information ◽  
Web Personalization ◽  
Current Trends ◽  
Technical Issues ◽  
Human Capability ◽  
Scientific Results ◽  
The Web

The Web has become a huge repository of information and keeps growing exponentially under no editorial control, while the human capability to find, read and understand content remains constant. Providing people with access to information is not the problem; the problem is that people with varying needs and preferences navigate through large Web structures, missing the goal of their inquiry. Web personalization is one of the most promising approaches for alleviating this information overload, providing tailored Web experiences. This chapter explores the different faces of personalization, traces back its roots and follows its progress. It describes the modules typically comprising a personalization process, demonstrates its close relation to Web mining, depicts the technical issues that arise, recommends solutions when possible, and discusses the effectiveness of personalization and the related concerns. Moreover, the chapter illustrates current trends in the field suggesting directions that may lead to new scientific results.

Web Personalization for E-Marketing Intelligence

2005 ◽  
pp. 48-68 ◽  
Author(s):  
Penelope Markellou ◽  
Maria Rigou ◽  
Spiros Sirmakessis
Keyword(s):  
Web Mining ◽  
Information Overload ◽  
User Interaction ◽  
Close Relation ◽  
Online Marketing ◽  
Web Personalization ◽  
Negative Effects ◽  
Comprehensive Overview ◽  
Research Issues ◽  
The Web

As the Web is growing exponentially, online marketing has been changed by the newly provided technological capacities and digital channels of sales. Online marketing or e-marketing is the adaptation and development of marketing strategies in the Web environment and includes all factors that affect a Web site’s efficiency, like the idea, the content, the structure, the interface, the implementation, the maintenance, the promotion and the advertising. Since more and more businesses are using the Web to conduct their activities, issues like interface usability, easy navigation and effective supporting services become critical and influence their success dramatically. However, one important problem that arises is that Web users are confronted with too many options. Currently, Web personalization is the most promising approach to alleviate this information overload and to provide users with tailored experiences. It improves user interaction with Web sites and offers them the ability to establish long-term and loyal relationships. The scope of this chapter is to give a comprehensive overview of research issues on personalized e-marketing applications. We focus on the importance of personalization as a remedy for the negative effects of the traditional “one-size-fits-all” approach. Next, we explore the different steps of the personalization process providing information about interesting research initiatives and representative commercial tools for producing personalized Web experiences. Finally, we demonstrate the close relation between personalization and Web mining and discuss open research issues.

Web Personalization for E-Marketing Intelligence

2009 ◽  
pp. 2164-2180 ◽  
Author(s):  
Penelope Markellou ◽  
Maria Rigou ◽  
Spiros Sirmakessis
Keyword(s):  
Web Mining ◽  
Information Overload ◽  
User Interaction ◽  
Close Relation ◽  
Online Marketing ◽  
Web Personalization ◽  
Negative Effects ◽  
Comprehensive Overview ◽  
Research Issues ◽  
The Web

As the Web is growing exponentially, online marketing has been changed by the newly provided technological capacities and digital channels of sales. Online marketing or e-marketing is the adaptation and development of marketing strategies in the Web environment and includes all factors that affect a Web site’s efficiency, like the idea, the content, the structure, the interface, the implementation, the maintenance, the promotion and the advertising. Since more and more businesses are using the Web to conduct their activities, issues like interface usability, easy navigation and effective supporting services become critical and influence their success dramatically. However, one important problem that arises is that Web users are confronted with too many options. Currently, Web personalization is the most promising approach to alleviate this information overload and to provide users with tailored experiences. It improves user interaction with Web sites and offers them the ability to establish long-term and loyal relationships. The scope of this chapter is to give a comprehensive overview of research issues on personalized e-marketing applications. We focus on the importance of personalization as a remedy for the negative effects of the traditional “one-size-fits-all” approach. Next, we explore the different steps of the personalization process providing information about interesting research initiatives and representative commercial tools for producing personalized Web experiences. Finally, we demonstrate the close relation between personalization and Web mining and discuss open research issues.

Semantic Web mining for Personalized Public Services

2007 ◽  
pp. 1-20
Author(s):  
Konstantinos Markellos ◽  
Penelope Markellou ◽  
Angeliki Panayiotaki ◽  
Athanasios Tsakalidis
Keyword(s):  
Semantic Web ◽  
Web Mining ◽  
Public Services ◽  
Web Environment ◽  
Current Trends ◽  
Scientific Results ◽  
The Web ◽  
The Way

As citizens are confronted with increasing volumes of information, boundless choices and endless opportunities in the Web environment, the need for personalized public e-services is more compulsory than ever. This chapter explores the way Semantic Web Mining technologies can be incorporated into public e-services domain in order to better meet citizens and authorities requirements. It describes the various steps of personalization process and examines techniques in use today to support it. In sequence, it introduces a recommendation scenario for an e-city portal. Finally, the chapter illustrates current trends in the field suggesting directions that may lead to new scientific results in the area.

scholarly journals Web Personalization With Web Usage Mining Technics and Association Rules

2015 ◽  
Vol 15 (1) ◽  
pp. 6394-6401 ◽  
Author(s):  
G. Kazeminuri ◽  
A. Harounabadi ◽  
J. Mirabedini
Keyword(s):  
Association Rules ◽  
Web Mining ◽  
Information Overload ◽  
Relevant Information ◽  
Web Personalization ◽  
Efficient Manner ◽  
Leading Role ◽  
Hidden Knowledge ◽  
Access To Data ◽  
The Web

As amount of information and web development increase considerably, some technics and methods are required to allow efficient access to data and information extraction from them. Extracting useful pattern from worldwide networks that are referred to as web mining is considered as one of the main applications of data mining. The key challenges of web users are exploring websites for finding the relevant information by taking minimum time in an efficient manner. Discovering the hidden knowledge in the manner of interaction in the web is considered as one of the most important technics in web utilization mining. Information overload is one of the main problems in current web and for tackling this problem the web personalization systems are presented that adapts the content and services of a website with user's interests and browsing behavior. Today website personalization is turned into a popular event for web users and it plays a leading role in speed of access and providing users' desirable information. The objective of current article is extracting index based on users' behavior and web personalization using web mining technics based on utilization and association rules. In proposed methods the weighting criteria showing the extent of interest of users to the pages are expressed and a method is presented based on combination of association rules and clustering by perceptron neural network for web personalization. The proposed method simulation results suggest the improvement of precision and coverage criteria with respect to other compared methods.

Web Mining for Public E-Services Personalization

2010 ◽  
pp. 751-758
Author(s):  
P. Markellou
Keyword(s):  
Web Site ◽  
Web Mining ◽  
Web Usage Mining ◽  
Web Content ◽  
Web Personalization ◽  
Business Transactions ◽  
Web Structure ◽  
Web Structure Mining ◽  
Content Mining ◽  
The Web

Over the last decade, we have witnessed an explosive growth in the information available on the Web. Today, Web browsers provide easy access to myriad sources of text and multimedia data. Search engines index more than a billion pages and finding the desired information is not an easy task. This profusion of resources has prompted the need for developing automatic mining techniques on Web, thereby giving rise to the term “Web mining” (Pal, Talwar, & Mitra, 2002). Web mining is the application of data mining techniques on the Web for discovering useful patterns and can be divided into three basic categories: Web content mining, Web structure mining, and Web usage mining. Web content mining includes techniques for assisting users in locating Web documents (i.e., pages) that meet certain criteria, while Web structure mining relates to discovering information based on the Web site structure data (the data depicting the Web site map). Web usage mining focuses on analyzing Web access logs and other sources of information regarding user interactions within the Web site in order to capture, understand and model their behavioral patterns and profiles and thereby improve their experience with the Web site. As citizens requirements and needs change continuously, traditional information searching, and fulfillment of various tasks result to the loss of valuable time spent in identifying the responsible actor (public authority) and waiting in queues. At the same time, the percentage of users who acquaint with the Internet has been remarkably increased (Internet World Stats, 2005). These two facts motivate many governmental organizations to proceed with the provision of e-services via their Web sites. The ease and speed with which business transactions can be carried out over the Web has been a key driving force in the rapid growth and popularity of e-government, e-commerce, and e-business applications. In this framework, the Web is emerging as the appropriate environment for business transactions and user-organization interactions. However, since it is a large collection of semi-structured and structured information sources, Web users often suffer from information overload. Personalization is considered as a popular solution in order to alleviate this problem and to customize the Web environment to users (Eirinaki & Vazirgiannis, 2003). Web personalization can be described, as any action that makes the Web experience of a user personalized to his or her needs and wishes. Principal elements of Web personalization include modeling of Web objects (pages) and subjects (users), categorization of objects and subjects, matching between and across objects and/or subjects, and determination of the set of actions to be recommended for personalization. In the remainder of this article, we present the way an e-government application can deploy Web mining techniques in order to support intelligent and personalized interactions with citizens. Specifically, we describe the tasks that typically comprise this process, illustrate the future trends, and discuss the open issues in the field.

Web Mining for Public E-Services Personalization

2009 ◽  
pp. 1079-1086 ◽  
Author(s):  
Penelope Markellou ◽  
Angeliki Panayiotaki ◽  
Athanasios Tsakalidis
Keyword(s):  
Web Site ◽  
Web Mining ◽  
Web Usage Mining ◽  
Web Content ◽  
Web Personalization ◽  
Business Transactions ◽  
Web Structure ◽  
Web Structure Mining ◽  
Content Mining ◽  
The Web

Over the last decade, we have witnessed an explosive growth in the information available on the Web. Today, Web browsers provide easy access to myriad sources of text and multimedia data. Search engines index more than a billion pages and finding the desired information is not an easy task. This profusion of resources has prompted the need for developing automatic mining techniques on Web, thereby giving rise to the term “Web mining” (Pal, Talwar, & Mitra, 2002). Web mining is the application of data mining techniques on the Web for discovering useful patterns and can be divided into three basic categories: Web content mining, Web structure mining, and Web usage mining. Web content mining includes techniques for assisting users in locating Web documents (i.e., pages) that meet certain criteria, while Web structure mining relates to discovering information based on the Web site structure data (the data depicting the Web site map). Web usage mining focuses on analyzing Web access logs and other sources of information regarding user interactions within the Web site in order to capture, understand and model their behavioral patterns and profiles and thereby improve their experience with the Web site. As citizens requirements and needs change continuously, traditional information searching, and fulfillment of various tasks result to the loss of valuable time spent in identifying the responsible actor (public authority) and waiting in queues. At the same time, the percentage of users who acquaint with the Internet has been remarkably increased (Internet World Stats, 2005). These two facts motivate many governmental organizations to proceed with the provision of e-services via their Web sites. The ease and speed with which business transactions can be carried out over the Web has been a key driving force in the rapid growth and popularity of e-government, e-commerce, and e-business applications. In this framework, the Web is emerging as the appropriate environment for business transactions and user-organization interactions. However, since it is a large collection of semi-structured and structured information sources, Web users often suffer from information overload. Personalization is considered as a popular solution in order to alleviate this problem and to customize the Web environment to users (Eirinaki & Vazirgiannis, 2003). Web personalization can be described, as any action that makes the Web experience of a user personalized to his or her needs and wishes. Principal elements of Web personalization include modeling of Web objects (pages) and subjects (users), categorization of objects and subjects, matching between and across objects and/or subjects, and determination of the set of actions to be recommended for personalization. In the remainder of this article, we present the way an e-government application can deploy Web mining techniques in order to support intelligent and personalized interactions with citizens. Specifically, we describe the tasks that typically comprise this process, illustrate the future trends, and discuss the open issues in the field.

World Wide Web Personalization

2011 ◽  
pp. 1235-1241 ◽  
Author(s):  
Olfa Nasraoui
Keyword(s):  
World Wide Web ◽  
World Wide ◽  
Information Overload ◽  
Information Age ◽  
Web Content ◽  
Web Personalization ◽  
Web Structure ◽  
Web Information ◽  
The World ◽  
The Web

The Web information age has brought a dramatic increase in the sheer amount of information (Web content), in the access to this information (Web usage), and in the intricate complexities governing the relationships within this information (Web structure). Hence, not surprisingly, information overload when searching and browsing the World Wide Web (WWW) has become the plague du jour. One of the most promising and potent remedies against this plague comes in the form of personalization. Personalization aims to customize the interactions on a Web site, depending on the user’s explicit and/or implicit interests and desires.

Web Mining for Public E-Services Personalization

2011 ◽  
pp. 1629-1634
Author(s):  
P. Markellou
Keyword(s):  
Web Site ◽  
Web Mining ◽  
Web Usage Mining ◽  
Web Content ◽  
Web Personalization ◽  
Business Transactions ◽  
Web Structure ◽  
Web Structure Mining ◽  
Content Mining ◽  
The Web

Over the last decade, we have witnessed an explosive growth in the information available on the Web. Today, Web browsers provide easy access to myriad sources of text and multimedia data. Search engines index more than a billion pages and finding the desired information is not an easy task. This profusion of resources has prompted the need for developing automatic mining techniques on Web, thereby giving rise to the term “Web mining” (Pal, Talwar, & Mitra, 2002). Web mining is the application of data mining techniques on the Web for discovering useful patterns and can be divided into three basic categories: Web content mining, Web structure mining, and Web usage mining. Web content mining includes techniques for assisting users in locating Web documents (i.e., pages) that meet certain criteria, while Web structure mining relates to discovering information based on the Web site structure data (the data depicting the Web site map). Web usage mining focuses on analyzing Web access logs and other sources of information regarding user interactions within the Web site in order to capture, understand and model their behavioral patterns and profiles and thereby improve their experience with the Web site. As citizens requirements and needs change continuously, traditional information searching, and fulfillment of various tasks result to the loss of valuable time spent in identifying the responsible actor (public authority) and waiting in queues. At the same time, the percentage of users who acquaint with the Internet has been remarkably increased (Internet World Stats, 2005). These two facts motivate many governmental organizations to proceed with the provision of e-services via their Web sites. The ease and speed with which business transactions can be carried out over the Web has been a key driving force in the rapid growth and popularity of e-government, e-commerce, and e-business applications. In this framework, the Web is emerging as the appropriate environment for business transactions and user-organization interactions. However, since it is a large collection of semi-structured and structured information sources, Web users often suffer from information overload. Personalization is considered as a popular solution in order to alleviate this problem and to customize the Web environment to users (Eirinaki & Vazirgiannis, 2003). Web personalization can be described, as any action that makes the Web experience of a user personalized to his or her needs and wishes. Principal elements of Web personalization include modeling of Web objects (pages) and subjects (users), categorization of objects and subjects, matching between and across objects and/or subjects, and determination of the set of actions to be recommended for personalization. In the remainder of this article, we present the way an e-government application can deploy Web mining techniques in order to support intelligent and personalized interactions with citizens. Specifically, we describe the tasks that typically comprise this process, illustrate the future trends, and discuss the open issues in the field.

Semantics and Agents Oriented Web Personalization

2016 ◽  
pp. 1018-1032
Author(s):  
Aarti Singh ◽  
Anu Sharma ◽  
Nilanjan Dey
Keyword(s):  
Semantic Web ◽  
Intelligent Agents ◽  
Web Mining ◽  
Information Overload ◽  
Software Agents ◽  
User Profile ◽  
Content Management ◽  
Multi Agent Systems ◽  
Web Personalization ◽  
Intelligent Software Agents

Advent of technologies like semantic web, multi-agent systems, web mining has changed the internet as knowledge provider. Web personalization offers a solution to the information overload problem in current web by providing users a personalized experience, considering their interest, behavior, context and emotions. Semantic web technology is based on use of software agents, ontologies and reasoning to add meaning to web information. An important technology for achieving personalization is the use of independent intelligent software agents. This work reviews, web personalization in the light of semantic web and software agent technology. A comparative study of recent works in the domain of web personalization has been carried out for this purpose. This review highlights ample scope for application of intelligent agents in the web personalization domain for solving many existing issues like personalized content management, user profile learning, modeling and adaptive interactions with users.

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