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- W2070767517 abstract "A novel text association rule approach FHAR algorithm is presented. To overcome the defect of traditional keywords which does not take into account the semantic relation between keywords, FHAR algorithm in the paper is based on concept vector. The density of semantic field and the weight of meaning are used to determine the concept of the keywords, which not only adds the texts semantic, but also reduces vector dimensions, FHAR algorithm adopts improved HASH table for efficient large item set generation. The stored address of item sets is determined by a new hash function. Based on the new hash table, tree structure is constructed. When FHAR algorithm is applied to text mining, the text association rule is derived. Experiments show FHAR algorithm possesses higher efficiency and accuracy than Apriori algorithm." @default.
- W2070767517 created "2016-06-24" @default.
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- W2070767517 date "2012-11-01" @default.
- W2070767517 modified "2023-10-16" @default.
- W2070767517 title "FHAR: A New Text Association Rule Algorithm Based on Concept Vector and Its Application" @default.
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- W2070767517 doi "https://doi.org/10.1109/mines.2012.113" @default.
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