عنوان

Web page recommendation models :

شابک

1608452484

شابک

9781608452484

شابک اشتباه

9781608452477

شماره

b789534

عنوان اصلي

Web page recommendation models :

نام عام مواد

[Book]

ساير اطلاعات عنواني

theory and algorithms /

نام نخستين پديدآور

Șule Gündüz-Ögüdücü.

محل نشرو پخش و غیره

San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) :

نام ناشر، پخش کننده و غيره

Morgan & Claypool,

تاریخ نشرو بخش و غیره

©2011.

نام خاص و کميت اثر

1 online resource (viii, 77 pages :

ساير جزييات

illustrations

عنوان فروست

Synthesis lectures on data management,

مشخصه جلد

# 10

شاپا ي ISSN فروست

2153-5426 ;

متن يادداشت

Part of: Synthesis digital library of engineering and computer science.

متن يادداشت

Series from website.

متن يادداشت

Includes bibliographical references (pages 69-75).

متن يادداشت

1. Introduction to web page recommender systems.

متن يادداشت

2. Preprocessing for web page recommender models -- Data collection -- Data preprocessing -- Web usage data preprocessing -- User and session identification -- Page time calculation -- Web content and structure data preprocessing -- Data model.

متن يادداشت

3. Pattern extraction -- Collaborative filtering -- Learning user preferences -- Association rules -- Clustering -- Page clusters -- Session clusters -- Sequential patterns -- Combination of web page recommender systems -- Combination methods -- Semantic web.

متن يادداشت

4. Evaluation metrics -- Bibliography -- Author's biography.

بدون عنوان

0

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

متن يادداشت

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.

منبع سفارش / آدرس اشتراک

Safari Books Online

شماره انبار

CL0500000343

عنوان

Web page recommendation models.

شماره استاندارد بين المللي کتاب و موسيقي

1608452476

موضوع مستند نشده

Recommender systems (Information filtering)

موضوع مستند نشده

Web sites-- Ratings and rankings.

موضوع مستند نشده

COMPUTERS-- Enterprise Applications-- Business Intelligence Tools.

موضوع مستند نشده

COMPUTERS-- Intelligence (AI) & Semantics.

موضوع مستند نشده

Recommender systems (Information filtering)

موضوع مستند نشده

Web sites-- Ratings and rankings.

موضوع مستند نشده

COM-- 004000

موضوع مستند نشده

COM-- 005030

شماره

ويراست

شماره رده

نشانه اثر

مستند نام اشخاص تاييد نشده

Gündüz-Ögüdücü, Șule.

تاريخ عمليات

20201207025918.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y