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Association Rules Based Short Text Feature Extension


Huang Wei, Li Shan-fei, Tan Yue-jin, Gao Bing


Vol. 9  No. 10  pp. 227-230


Focused on the effect on classification of short text sparse features, propose a method extending the short text features. First, according to the theory of words co- occurrence model, the association rules between feature items of corpus are mined by FP-growth algorithm. Then, we search the rules in the set of association rules, which have the relationship with short text feature items, calculate the mutual information between the antecedent and subsequent of association rules, and estimate the degree of association between two features. Based on these work, we choose short text extension feature words and construct the collection of the short text features. Experiments show that the efficiency of short text classification is improved after extending the short text features.


Association Rules, Short Text, Text Feature, Extension