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Multi-label document classification concerns the determination of categories in the situation where one document may belong to more than one category. In this paper we propose a fuzzy similarity-based approach for multi-label document classification. For a test document, the scores of its relevance to the classes are calculated based on a modified fuzzy similarity measure. The test document is then decided to belong to every class whose score passes a threshold. To make the system adaptive, we provide a heuristic approach to find a score threshold automatically for each class. Experimental results show that our proposed method is more effective and efficient than other existing methods.
Computer Science and Engineering, 2009. WCSE '09. Second International Workshop on (Volume:2 )
Date of Conference: 28-30 Oct. 2009