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Web recommendations systems
~
Santosh Nimbhorkar, Sejal.
Web recommendations systems
Record Type:
Electronic resources : Monograph/item
Title/Author:
Web recommendations systemsby K. R. Venugopal, K. C. Srikantaiah, Sejal Santosh Nimbhorkar.
Author:
Venugopal, K. R.
other author:
Srikantaiah, K. C.
Published:
Singapore :Springer Singapore :2020.
Description:
xxi, 164 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Recommender systems (Information filtering)
Online resource:
https://doi.org/10.1007/978-981-15-2513-1
ISBN:
9789811525131$q(electronic bk.)
Web recommendations systems
Venugopal, K. R.
Web recommendations systems
[electronic resource] /by K. R. Venugopal, K. C. Srikantaiah, Sejal Santosh Nimbhorkar. - Singapore :Springer Singapore :2020. - xxi, 164 p. :ill., digital ;24 cm.
1 Introduction -- 2 Web Data Extraction and Integration System for Search Engine Result Pages -- 3 Mining and Analysis of Web Sequential Patterns -- 4 Automatic Discovery and Ranking of Synonyms for Search Keywords in the Web -- 5 Construction of Topic Directories using Levenshtein Similarity Weight -- 6 Related Search Recommendation with User Feedback Session -- 7 Webpage Recommendations based Web Navigation Prediction.
This book focuses on Web recommender systems, offering an overview of approaches to develop these state-of-the-art systems. It also presents algorithmic approaches in the field of Web recommendations by extracting knowledge from Web logs, Web page content and hyperlinks. Recommender systems have been used in diverse applications, including query log mining, social networking, news recommendations and computational advertising, and with the explosive growth of Web content, Web recommendations have become a critical aspect of all search engines. The book discusses how to measure the effectiveness of recommender systems, illustrating the methods with practical case studies. It strikes a balance between fundamental concepts and state-of-the-art technologies, providing readers with valuable insights into Web recommender systems.
ISBN: 9789811525131$q(electronic bk.)
Standard No.: 10.1007/978-981-15-2513-1doiSubjects--Topical Terms:
310886
Recommender systems (Information filtering)
LC Class. No.: ZA3084 / .V45 2020
Dewey Class. No.: 005.56
Web recommendations systems
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1 Introduction -- 2 Web Data Extraction and Integration System for Search Engine Result Pages -- 3 Mining and Analysis of Web Sequential Patterns -- 4 Automatic Discovery and Ranking of Synonyms for Search Keywords in the Web -- 5 Construction of Topic Directories using Levenshtein Similarity Weight -- 6 Related Search Recommendation with User Feedback Session -- 7 Webpage Recommendations based Web Navigation Prediction.
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This book focuses on Web recommender systems, offering an overview of approaches to develop these state-of-the-art systems. It also presents algorithmic approaches in the field of Web recommendations by extracting knowledge from Web logs, Web page content and hyperlinks. Recommender systems have been used in diverse applications, including query log mining, social networking, news recommendations and computational advertising, and with the explosive growth of Web content, Web recommendations have become a critical aspect of all search engines. The book discusses how to measure the effectiveness of recommender systems, illustrating the methods with practical case studies. It strikes a balance between fundamental concepts and state-of-the-art technologies, providing readers with valuable insights into Web recommender systems.
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EB ZA3084 .V471 2020 2020
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https://doi.org/10.1007/978-981-15-2513-1
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