Because of the fact that the introductions of primary and secondary schools have less feature items and unequal weights, the authors use the strategies of denoising, processing synonym features based on fuzzy set to build category vocabularies, and then classify short texts using the classification model which is based on category vocabularies and fuzzy rules. The results show that using fuzzy rules to classify the short texts which have less feature items and uneven distribution of weight is better than VSM, Rocchio and other classification algorithms.
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Liang Wenchao, Xu Chaojun, Shen Shusheng. Application of the Fuzzy Rule Algorithm in the Classification of Educational Information. New Technology of Library and Information Service, 2011, 27(1): 94-98.
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