Searching and Browsing Tag Spaces Using the Semantic Tag Clustering Search Framework

J-W van Dam, Damir Vandic, Frederik Hogenboom, Flavius Frasincar

Research output: Contribution to conferencePosterAcademic

17 Citations (Scopus)

Abstract

Many of the existing cloud tagging systems are unable to cope with the syntactic and semantic tag variations during user search and browse activities. As a solution to this problem, in this paper, we propose the Semantic Tag Clustering Search, a framework able to cope with these needs. The framework consists of three parts: removing syntactic variations, creating semantic clusters, and utilizing the obtained clusters to improve search and exploration of tag spaces. For removing syntactic variations, we use the normalized Levenshtein distance, and the cosine similarity measure based on tag co-occurrences. For creating semantic clusters, we improve an existing non-hierarchical clustering technique. Using our framework, we are able to find more clusters and achieve a higher precision than the original method. The advantages of a cluster-based approach for searching and browsing through tag spaces have been exploited in XploreFlickr.com, the implementation of our framework.
Original languageEnglish
Pages436-439
Number of pages4
DOIs
Publication statusPublished - 22 Sep 2010
EventFourth IEEE International Conference on Semantic Computing (ICSC 2010) -
Duration: 22 Sep 201024 Sep 2010

Conference

ConferenceFourth IEEE International Conference on Semantic Computing (ICSC 2010)
Period22/09/1024/09/10

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