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pro vyhledávání: '"Shian-Chi Tsai"'
Autor:
Shian-Chi Tsai, 蔡憲奇
98
Unlike single-label document classification, where each document exactly belongs to a single category, when the document is classified into two or more categories, known as multi-label file, how to classify such documents accurately has becom
Unlike single-label document classification, where each document exactly belongs to a single category, when the document is classified into two or more categories, known as multi-label file, how to classify such documents accurately has becom
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/31662748044494901477
Publikováno v:
Expert Systems with Applications. 39:2813-2821
We propose an efficient approach, FSKNN, which employs fuzzy similarity measure (FSM) and k nearest neighbors (KNN), for multi-label text classification. One of the problems associated with KNN-like approaches is its demanding computational cost in f
Publikováno v:
2010 International Conference on Technologies and Applications of Artificial Intelligence.
Multi-label classification learning concerns the determination of categories in the situation where one pattern may belong to more than one category. In this paper we propose a mixture approach, named FSMLKNN, which combines Fuzzy Similarity Measure
Publikováno v:
2009 Second International Workshop on Computer Science and Engineering.
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.
Publikováno v:
Second International Workshop on Computer Science & Engineering, 2009. WCSE '09; 2009, p59-63, 5p