Web Page Recommendation Models (Record no. 84609)

000 -LEADER
fixed length control field 03548nam a22004935i 4500
001 - CONTROL NUMBER
control field 978-3-031-01842-8
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240730163436.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220601s2011 sz | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783031018428
-- 978-3-031-01842-8
082 04 - CLASSIFICATION NUMBER
Call Number 004.6
100 1# - AUTHOR NAME
Author Gunduz-Oguducu, Sule.
245 10 - TITLE STATEMENT
Title Web Page Recommendation Models
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2011.
300 ## - PHYSICAL DESCRIPTION
Number of Pages VII, 77 p.
490 1# - SERIES STATEMENT
Series statement Synthesis Lectures on Data Management,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction to Web Page Recommender Systems -- Preprocessing for Web Page Recommender Models -- Pattern Extraction -- Evaluation Metrics.
520 ## - SUMMARY, ETC.
Summary, etc 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.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1007/978-3-031-01842-8
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Koha item type eBooks
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-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2011.
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-- txt
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-- computer
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-- rdamedia
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-- online resource
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-- text file
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer networks .
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data structures (Computer science).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Information theory.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer Communication Networks.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Data Structures and Information Theory.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 2153-5426
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-- ZDB-2-SXSC

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