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Web recommendations systems

Venugopal, K. R.

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Web recommendations systems

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Web recommendations systems/ by K. R. Venugopal, K. C. Srikantaiah, Sejal Santosh Nimbhorkar.
作者:	Venugopal, K. R.
其他作者:	Srikantaiah, K. C.
出版者:	Singapore :Springer Singapore : : 2020.,
面頁冊數:	xxi, 164 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Recommender systems (Information filtering) -
電子資源:	https://doi.org/10.1007/978-981-15-2513-1
ISBN:	9789811525131

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

Standard No.: 10.1007/978-981-15-2513-1doiSubjects--Topical Terms:

1002434
Recommender systems (Information filtering)

LC Class. No.: ZA3084 / .V45 2020

Dewey Class. No.: 005.56

Web recommendations systems
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505 0 $a 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.
520 $a 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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650 2 4 $a Data Structures. $3 891009
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