Web Page Recommendation Models / by Sule Gunduz-Oguducu.

Format:

Book

Author/Creator:

Gündüz-Ögüdücü, Şule, Author.

Series:

Synthesis Lectures on Data Management, 2153-5426

Language:

English

Subjects (All):

Computer networks.

Data structures (Computer science).

Information theory.

Computer Communication Networks.

Data Structures and Information Theory.

Local Subjects:

Computer Communication Networks.

Data Structures and Information Theory.

Physical Description:

1 online resource (VII, 77 p.)

Edition:

1st ed. 2011.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2011.

System Details:

Mode of access: World Wide Web.

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

Contents:

Introduction to Web Page Recommender Systems

Preprocessing for Web Page Recommender Models

Pattern Extraction

Evaluation Metrics.

Notes:

Includes bibliographical references and index.

ISBN:

9783031018428

3031018427