Web page recommendation models : theory and algorithms
- Responsibility
- Șule Gündüz-Ögüdücü.
- Language
- English. English.
- Imprint
- Cham, Switzerland : Springer, ©2011.
- Physical description
- 1 online resource (viii, 77 pages : illustrations
- Series
- Synthesis digital library of engineering and computer science.
- Synthesis lectures on data management ; # 10. 2153-5426
Online
Available online
More options
Description
Creators/Contributors
- Author/Creator
- Gündüz-Ögüdücü, Șule.
Contents/Summary
- Bibliography
- Includes bibliographical references (pages 69-75).
- Contents
-
- Introduction to Web Page Recommender Systems Preprocessing for Web Page Recommender Models Pattern Extraction Evaluation Metrics.
- (source: Nielsen Book Data)
- Publisher's summary
-
One of the application areas of data mining is the World Wide Web (WWW or Web), which serves as a huge, widely distributed, global information service for every kind of information such as news, advertisements, consumer information, financial management, education, government, e-commerce, health services, and many other information services. The Web also contains a rich and dynamic collection of hyperlink information, Web page access and usage information, providing sources for data mining. The amount of information on the Web is growing rapidly, as well as the number of Web sites and Web pages per Web site. Consequently, it has become more difficult to find relevant and useful information for Web users. Web usage mining is concerned with guiding the Web users to discover useful knowledge and supporting them for decision-making. In that context, predicting the needs of a Web user as she visits Web sites has gained importance. The requirement for predicting user needs in order to guide the user in a Web site and improve the usability of the Web site can be addressed by recommending pages to the user that are related to the interest of the user at that time. This monograph gives an overview of the research in the area of discovering and modeling the users' interest in order to recommend related Web pages. The Web page recommender systems studied in this monograph are categorized according to the data mining algorithms they use for recommendation.
(source: Nielsen Book Data)
Subjects
- Subjects
- Recommender systems (Information filtering)
- Web sites > Ratings and rankings.
- Systèmes de recommandation (Filtrage d'information)
- Sites Web > Classement.
- COMPUTERS > Enterprise Applications > Business Intelligence Tools.
- COMPUTERS > Intelligence (AI) & Semantics.
- Web page recommendation
- Web structure mining
- Web content mining
- Web log mining
- Semantic Web mining
- Web log data cleaning
- Web log data preparation
- Collaborative filtering
- Pattern extraction
- Evaluation methods
Bibliographic information
- Publication date
- 2011
- Series
- Synthesis lectures on data management, 2153-5426 ; # 10
- Note
- Part of: Synthesis digital library of engineering and computer science.
- Series from website.
- Referenced in
- Compendex
- INSPEC
- Google scholar
- Google book search
- ISBN
- 9781608452484 (electronic bk.)
- 1608452484 (electronic bk.)
- 9781608452477 (pbk.)
- 9783031018428 (electronic bk.)
- 3031018427 (electronic bk.)
- DOI
- 10.2200/S00305ED1V01Y201010DTM010
- 10.1007/978-3-031-01842-8
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