Collaborative Tagging in Recommender Systems

This paper proposes a collaborative filtering method with user-created tags focusing on changes of web content and internet services. Collaborative tagging is employed as an approach in order to grasp and filter users’ preferences for items. In addition, we explore several advantages of collaborativ...

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Bibliographic Details
Published inAI 2007: Advances in Artificial Intelligence Vol. 4830; pp. 377 - 386
Main Authors Ji, Ae-Ttie, Yeon, Cheol, Kim, Heung-Nam, Jo, Geun-Sik
Format Book Chapter
LanguageEnglish
Published Germany Springer Berlin / Heidelberg 2007
Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Artificial intelligence
Collaborative Filter
Collaborative Filter Algorithm
Data mining
Mathematical theory of computation
Recommendation Algorithm
Recommender System
Target User
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ISBN9783540769262
3540769269
ISSN0302-9743
1611-3349
DOI10.1007/978-3-540-76928-6_39

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Summary:This paper proposes a collaborative filtering method with user-created tags focusing on changes of web content and internet services. Collaborative tagging is employed as an approach in order to grasp and filter users’ preferences for items. In addition, we explore several advantages of collaborative tagging for future searching and information sharing which is used for automatic analysis of user preference and recommendation. We present empirical experiments using real dataset from del.icio.us to demonstrate our algorithm and evaluate performance compared with existing works.
ISBN:9783540769262
3540769269
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-540-76928-6_39