The purpose of this study is to compare performance among developed subject discrimination methods for educational Web resources. Three methods are vector space model (VSM) using degree of cosine similarity, vector distance on the self-organizing map (SOM) and three layer percptron (MLP). The 403 teaching schemes were prepared as the test documents for the subject discrimination. The recall rate using MLP is the highest for most subjects. The highest precision rate among the methods depend on subject. As a result, Fl measure as total performance index of most subjects are the highest for the method using MLP.
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