Cluster-Based Information Retrieval in Tag Spaces

Many of the existing tagging systems fail to cope with syntactic and semantic tag variations during user search and browse activities. As a solution to this problem, we propose the Semantic Tag Clustering Search. 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. Using our framework, we are able to find relevant clusters and achieve a higher search precision by utilizing these clusters. 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.