Research of Adaptive Text Fuzzy Clustering Method Based on Genetic Algorithm
As Fuzzy C-means Clustering Algorithm is sensitive to the choice of the initial cluster centers and.t’s difficult to determine the cluster number,we proposed an Adaptive Text Fuzzy Clustering Method Based on Genetic Algorithm.According to the principle of Vector Space Model,documents were represented as vectors.Then we adopted a new strategy of variable-length chromosome encoding and randomly chose initial clustering centers to form chromosomes among document vectors.Combining the emciency of Fuzzy C-means Algorithm with the global optimization abihty of Genetic Algorithm.the local optimal solution was avoided and the optimum number and the optimum result of cluster were obtained by means of genetic evolution.Experiments indicated that this algorithm Was efficient and accurate.
Fuzzy Clustering Genetic Algorithm Text Clustering Variable-length Chromosome
Wenhua Dai Cuizhen Jiao Tingting He
国际会议
The International Conference Information Computing and Automation(2007国际信息计算与自动化会议)
成都
英文
1270-1273
2007-12-19（万方平台首次上网日期，不代表论文的发表时间）