Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Latent subject-centered modeling of collaborative tagging: An application in social search

Latent subject-centered modeling of collaborative tagging: An application in social search Latent Subject-Centered Modeling of Collaborative Tagging: An Application in Social Search JING PENG, Chinese Academy of Sciences DANIEL D. ZENG, Chinese Academy of Sciences and University of Arizona ZAN HUANG, The Pennsylvania State University Collaborative tagging or social bookmarking is a main component of Web 2.0 systems and has been widely recognized as one of the key technologies underpinning next-generation knowledge management platforms. In this article, we propose a subject-centered model of collaborative tagging to account for the ternary cooccurrences involving users, items, and tags in such systems. Extending the well-established probabilistic latent semantic analysis theory for knowledge representation, our model maps the user, item, and tag entities into a common latent subject space that captures the œwisdom of the crowd  resulted from the collaborative tagging process. To put this model into action, we have developed a novel way to estimate the probabilistic subject-centered model approximately in a highly ef cient manner taking advantage of a matrix factorization method. Our empirical evaluation shows that our proposed approach delivers substantial performance improvement on the knowledge resource recommendation task over the state-of-the-art standard and tag-aware resource recommendation algorithms. Categories and Subject Descriptors: H.3.3 [Information Storage and Retrieval]: Information Search http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png ACM Transactions on Management Information Systems (TMIS) Association for Computing Machinery

Latent subject-centered modeling of collaborative tagging: An application in social search

Download PDF
23 pages

Loading next page...
 
/lp/association-for-computing-machinery/latent-subject-centered-modeling-of-collaborative-tagging-an-FNWFjdks5M

References (66)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2011 by ACM Inc.
ISSN
2158-656X
DOI
10.1145/2019618.2019621
Publisher site
See Article on Publisher Site

Abstract

Latent Subject-Centered Modeling of Collaborative Tagging: An Application in Social Search JING PENG, Chinese Academy of Sciences DANIEL D. ZENG, Chinese Academy of Sciences and University of Arizona ZAN HUANG, The Pennsylvania State University Collaborative tagging or social bookmarking is a main component of Web 2.0 systems and has been widely recognized as one of the key technologies underpinning next-generation knowledge management platforms. In this article, we propose a subject-centered model of collaborative tagging to account for the ternary cooccurrences involving users, items, and tags in such systems. Extending the well-established probabilistic latent semantic analysis theory for knowledge representation, our model maps the user, item, and tag entities into a common latent subject space that captures the œwisdom of the crowd  resulted from the collaborative tagging process. To put this model into action, we have developed a novel way to estimate the probabilistic subject-centered model approximately in a highly ef cient manner taking advantage of a matrix factorization method. Our empirical evaluation shows that our proposed approach delivers substantial performance improvement on the knowledge resource recommendation task over the state-of-the-art standard and tag-aware resource recommendation algorithms. Categories and Subject Descriptors: H.3.3 [Information Storage and Retrieval]: Information Search

Journal

ACM Transactions on Management Information Systems (TMIS) – Association for Computing Machinery

Published: Oct 1, 2011

There are no references for this article.