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Web mining for web personalization
- ACM Transactions on Internet Technology
, 2003
"... Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user’s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content an ..."
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Cited by 217 (6 self)
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Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user’s navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. In this article we present a survey of the use of Web mining for Web personalization. More specifically, we introduce the modules that comprise a Web personalization system, emphasizing the Web usage mining module. A review of the most common methods that are used as well as technical issues that occur is given, along with a brief overview of the most popular tools and applications available from software vendors. Moreover, the most important research initiatives in the Web usage mining and personalization areas are presented.
Towards Adaptive Web Sites: Conceptual Framework and Case Study
- ARTIFICIAL INTELLIGENCE
, 2000
"... The creation of a complex web site is a thorny problem in user interface design. In this paper we explore the notion of adaptiveweb sites: sites that semi-automatically improve their organization and presentation by learning from visitor access patterns. It is easy to imagine and implementweb sit ..."
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Cited by 198 (4 self)
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The creation of a complex web site is a thorny problem in user interface design. In this paper we explore the notion of adaptiveweb sites: sites that semi-automatically improve their organization and presentation by learning from visitor access patterns. It is easy to imagine and implementweb sites that offer shortcuts to popular pages. Are more sophisticated adaptiveweb sites feasible? What degree of automation can weachieve? To address the questions above, we describe the design space of adaptiveweb sites and consider a case study: the problem of synthesizing new index pages that facilitate navigation of a web site. We presentthePageGather algorithm, which automatically identifies candidate link sets to include in index pages based on user access logs. We demonstrate experimentally that PageGather outperforms the Apriori data mining algorithm on this task. In addition, we compare PageGather's link sets to pre-existing, human-authored index pages.
Knowledge-Based Recommender Systems
- ENCYCLOPEDIA OF LIBRARY AND INFORMATION SYSTEMS
, 2000
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Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
- Data Mining and Knowledge Discovery
, 2002
"... Web usage mining, possibly used in conjunction with standard approaches to personalization such as collaborative filtering, can help address some of the shortcomings of these techniques, including reliance on subjective user ratings, lack of scalability, and poor performance in the face of high-dime ..."
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Cited by 142 (15 self)
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Web usage mining, possibly used in conjunction with standard approaches to personalization such as collaborative filtering, can help address some of the shortcomings of these techniques, including reliance on subjective user ratings, lack of scalability, and poor performance in the face of high-dimensional and sparse data. However, the discovery of patterns from usage data by itself is not sufficient for performing the personalization tasks. The critical step is the effective derivation of good quality and useful (i.e., actionable) "aggregate usage profiles" from these patterns. In this paper we present and experimentally evaluate two techniques, based on clustering of user transactions and clustering of pageviews, in order to discover overlapping aggregate profiles that can be effectively used by recommender systems for real-time Web personalization. We evaluate these techniques both in terms of the quality of the individual profiles generated, as well as in the context of providing recommendations as an integrated part of a personalization engine. In particular, our results indicate that using the generated aggregate profiles, we can achieve effective personalization at early stages of users' visits to a site, based only on anonymous clickstream data and without the benefit of explicit input by these users or deeper knowledge about them.
Effective personalization based on association rule discovery from web usage data. In:
- Proceedings of the 3rd International Workshop on Web Information and Data Management,
, 2001
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Integrating Web Usage and Content Mining for More Effective Personalization
- IN E-COMMERCE AND WEB TECHNOLOGIES," LECTURE NOTES IN COMPUTER SCIENCE (LNCS) 1875
, 2000
"... Recent proposals have suggested Web usage mining as an enabling mechanism to overcome the problems associated with more traditional Web personalization techniques such as collaborative or contentbased filtering. These problems include lack of scalability, reliance on subjective user ratings or s ..."
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Cited by 105 (10 self)
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Recent proposals have suggested Web usage mining as an enabling mechanism to overcome the problems associated with more traditional Web personalization techniques such as collaborative or contentbased filtering. These problems include lack of scalability, reliance on subjective user ratings or static profiles, and the inability to capture a richer set of semantic relationships among objects (in content-based systems). Yet, usage-based personalization can be problematic when little usage data is available pertaining to some objects or when the site contentchanges regularly.For more effective personalization, both usage and content attributes of a site must be integrated into a Web mining framework and used by the recommendation engine in a uniform manner. In this
Web Usage Mining: Discovery and Application of Interestin Patterns from Web Data
, 2000
"... Web Usage Mining is the application of data mining techniques to Web clickstream data in order to extract usage patterns. As Web sites continue to grow in size and complexity, the results of Web Usage Mining have become critical for a number of applications such as Web site design, business and mark ..."
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Cited by 102 (0 self)
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Web Usage Mining is the application of data mining techniques to Web clickstream data in order to extract usage patterns. As Web sites continue to grow in size and complexity, the results of Web Usage Mining have become critical for a number of applications such as Web site design, business and marketing decision support, personalization, usability studies, and network trac analysis. The two major challenges involved in Web Usage Mining are preprocessing the raw data to provide an accurate picture of how a site is being used, and ltering the results of the various data mining algorithms in order to present only the rules and patterns that are potentially interesting. This thesis develops and tests an architecture and algorithms for performing Web Usage Mining. An evidence combination framework referred to as the information lter is developed to compare and combine usage, content, and structure information about a Web site. The information lter automatically identi es the discovered ...
A Survey of Web Metrics
- ACM COMPUTING SURVEYS
, 2002
"... ... this article, we examine this issue by classifying and discussing a wide ranging set of Web metrics. We present the origins, measurement functions, formulations and comparisons of well-known Web metrics for quantifying Web graph properties, Web page significance, Web page similarity, search a ..."
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Cited by 90 (0 self)
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... this article, we examine this issue by classifying and discussing a wide ranging set of Web metrics. We present the origins, measurement functions, formulations and comparisons of well-known Web metrics for quantifying Web graph properties, Web page significance, Web page similarity, search and retrieval, usage characterization and information theoretic properties. We also discuss how these metrics can be applied for improving Web information access and use.
Finding Replicated Web Collections
- ACM SIGMOD
, 2000
"... Paper Number 201 Many web documents (such as JAVA FAQs) are being replicated on the Internet. Often entire document collections (such as hyperlinked Linux manuals) are being replicated many times. In this paper, we make the case for identifying replicated documents and collections to improve web cra ..."
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Cited by 78 (4 self)
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Paper Number 201 Many web documents (such as JAVA FAQs) are being replicated on the Internet. Often entire document collections (such as hyperlinked Linux manuals) are being replicated many times. In this paper, we make the case for identifying replicated documents and collections to improve web crawlers, archivers, and ranking functions used in search engines. The paper describes how to efficiently identify replicated documents and hyperlinked document collections. The challenge is to identify these replicas from an input data set of several tens of millions of web pages and several hundreds of gigabytes of textual data. We also present two real-life case studies where we used replication information to improve a crawler and a search engine. We report these results for a data set of 25 million web pages (about 150 gigabytes of HTML data) crawled from the web.
Discovery of aggregate usage profiles for web personalization.
- In Proceedings of the Workshop on Web Mining for E-Commerce (WEBKDD’00),
, 2000
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