Aussie-Sino Studies

2017, (1) P87-P91

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Semi-supervised Text Classification Research Based on Ant Colony algorithm

Han Yu, Li Meicong, Dang Hongpeng

摘要(Abstract):

In view of the characteristics of sparse sexual text classification, this paper proposes a kind of semi-supervised text classification algorithm based on the characteristics of ant colony algorithm. The method applied in this paper is to increase the effect factor of the concentration of pheromone ant colony aggregation to extended ant pheromone diffusion mode and propose the ant population marker based on Top-k strategy and randomly selected candidate judgment confidence into the ant population classification. This paper selects the 20 Newsgroups corpus for experimental test and EM algorithm as compared algorithm. It has obvious advantages in terms of the index of F-1 degree as well as precision ratio and the recall ratio.

关键词(KeyWords): Semi-supervised; Text classification; Ant colony algorithm

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作者(Author): Han Yu, Li Meicong, Dang Hongpeng

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