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The existing tag based system deducts a retrieval result with low accuracy through the usage of a single tag matching by using tags tagged in contents. And the system doesn`t provide effectively contents related information which the tags have, as the users place tags on contents without considering the priority and associative relation between tags. For a solve of above problems, this paper suggests a tag ranking system which extracts semantic similarity between tags and re-ranks the tags tagged in contents. In order to evaluate the performance of suggested system, this paper experiments and compares the ranking result of this paper`s tag ranking system with the result of baseline method using tags tagged in images and frequency method adapting tag co-appearance frequency.

Tag Ranking System based on Semantic Similarity of Tag-pair