Title
Collaborative resource discovery in social tagging systems
Abstract
Social tagging systems which allow users to create, edit and share collections of internet resources associated with tags in a collaborative fashion are growing in popularity in recent years. The rapidly growing amount of shared data in these folksonomies, i.e., taxonomies created by the folk, presents new technical challenges involved with discovering resources which are likely of interest to the user. Social tags which reflect the meaning of resources from the user's points of view provide an opportunity to enhance the quality of retrieval. In this paper, we introduce a novel framework to search relevant resources to the user query by incorporating information obtained from folksonomies' underlying data structures consisting of a set of user/tag/resource triplets. In contrast to traditional retrieval and recommendation techniques which represent a collection by a matrix, we represent our data as a third-order tensor on which a novel Cube Latent Semantic Indexing (CubeLSI) technique is proposed to capture latent semantic associations between tags. With the latent semantic representation we show how to rank relevant resources according to their relevance to user queries. The excellent performance of the method is demonstrated by an experimental evaluation on the deli.cio.us dataset.
Year
DOI
Venue
2009
10.1145/1645953.1646265
CIKM
Keywords
Field
DocType
novel cube latent semantic,relevant resource,latent semantic association,shared data,latent semantic representation,novel framework,collaborative resource discovery,underlying data structure,user query,social tagging system,social tag,data structure,tucker decomposition,tensor,svd,latent semantic indexing
Data structure,Data mining,Latent semantic indexing,World Wide Web,Information retrieval,Computer science,Popularity,Probabilistic latent semantic analysis,Social tags,Semantic representation,Internet resources
Conference
Citations 
PageRank 
References 
6
0.50
7
Authors
3
Name
Order
Citations
PageRank
Bin Bi1965.26
Lifeng Shang248530.96
Ben Kao32358194.98