Clustering the tagged resources using STAC

Authors:
Feihang Gao;Kening Gao;Bin Zhang
Affiliations:
College of Information Science and Technology, Northeastern University, Shenyang, China;College of Information Science and Technology, Northeastern University, Shenyang, China;College of Information Science and Technology, Northeastern University, Shenyang, China
Venue:
WISM'10 Proceedings of the 2010 international conference on Web information systems and mining
Year:
2010

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Abstract

Similarity calculation is a key step in the process of clustering. Because most tagged resources on the Internet lack text information, traditional similarity measures cannot obtain good results. We propose the STAC measure to solve the problem of calculating the similarity between tagged resources. In the calculation of STAC, the similarity between tags is calculated using tag co-occurrence information, and the similarity between tagged resources is calculated based on tag comparison. Experiments show the clustering results of tagged resources using STAC is significantly better than using other traditional metrics such as the Euclidean distance and Jaccard coefficient.