Web Recommendation System Based on Users Searching History

Language: English

Published by Scholars' Press, 2018

6202311339 / 9786202311335

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nach der Bestellung gedruckt Neuware - Printed after ordering - Presently, most of the available recommendation system uses collaborative filtering approach. These type of recommender systems assumes that if two users have shown similar interest on the same set of contents, they may show a similar interest pattern in choosing future contents. However, it may happen that the users who have certain tastes on one specific category of contents may behave differently in choosing contents from other categories. Also, the collaborative filtering approaches do not work efficiently with sparse data sets, where there are a small number of contents or a limited number of users in the content categories. To overcome all these problems, a novel approach of recommending contents across different categories by considering both the semantic information of contents and user interests is used. This approach uses Linked Data as the source to find the appropriate semantics of the contents extracted from users viewing history. The semantic concepts retrieved for the contents are then grouped together into semantic clusters based on their similarity and relevance.

Seller Inventory # 9786202311335

Title
Web Recommendation System Based on Users Searching History
Author
Gaurav Paliwal
Publisher
Scholars' Press
Publication year
2018
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6202311339
ISBN 13
9786202311335
Item weight
113 grams
Dimensions
220x150x4 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

Item30 to 40 business days7 to 14 business days
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