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, we propose the Semantic Tag Clustering Search, a framework which is able to cope with these needs. The framework consists of two parts: removing syntactic variations and creating semantic clusters. 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.

Flickr, Semantic clustering, Syntactic variations, Tag spaces
dx.doi.org/10.1109/ICSC.2010.32, hdl.handle.net/1765/23890
ERIM report series research in management Erasmus Research Institute of Management
Erasmus Research Institute of Management

Van Dam, J.W, Vandic, D, Hogenboom, F.P, & Frasincar, F. (2010). Searching and browsing tag spaces using the semantic tag clustering search framework. ERIM report series research in management Erasmus Research Institute of Management, 436–439. doi:10.1109/ICSC.2010.32