Web Page Recommendation Models
eBook - PDF

Web Page Recommendation Models

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Web Page Recommendation Models

Book details
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About This Book

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 guidethe 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. Table of Contents: Introduction to Web Page Recommender Systems / Preprocessing for Web Page Recommender Models / Pattern Extraction / Evaluation Metrics

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Yes, you can access Web Page Recommendation Models by Sule Gunduz-Oguducu in PDF and/or ePUB format, as well as other popular books in Computer Science & Computer Networking. We have over one million books available in our catalogue for you to explore.

Information

Publisher
Springer
Year
2022
ISBN
9783031018428
Topic
Computer Science
Subtopic
Computer Networking
Index
Computer Science

Table of contents

  1. Cover
  2. Copyright Page
  3. Title Page
  4. Contents
  5. Introduction to Web Page Recommender Systems
  6. Preprocessing for Web Page Recommender Models
  7. Pattern Extraction
  8. Evaluation Metrics
  9. Bibliography
  10. Author's Biography