| 基于模糊聚类的文本挖掘算法 |
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| 引用本文： | 刘志勇,耿新青. 基于模糊聚类的文本挖掘算法[J]. 计算机工程, 2009, 35(5): 44-45,4 |
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| 作者姓名： | 刘志勇 耿新青 |
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| 作者单位： | 大连理工大学管理学院,大连,116024;鞍山师范学院数学系,鞍山,114005;鞍山师范学院数学系,鞍山,114005 |
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| 摘 要： | 针对传统FCM算法对孤立点比较敏感，须预先指定聚类数目的缺陷，提出一种新的模糊聚类算法NSFCM，将其应用干文本挖掘中。NSFCM对数据对象的隶属度增加一个权值，以减少孤立点对聚类中心的影响。采用平均信息熵确定聚类数，通过密度函数获得初始聚类中心。仿真结果证明，该算法聚类的精度和执行效率均高于FCM算法，效果较好。
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| 关 键 词： | 聚类数 文本聚类 模糊聚类 |
| 修稿时间： | |
Text Mining Algorithm Based on Fuzzy Clustering |
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| LIU Zhi-yong,GENG Xin-qing. Text Mining Algorithm Based on Fuzzy Clustering[J]. Computer Engineering, 2009, 35(5): 44-45,4 |
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| Authors: | LIU Zhi-yong GENG Xin-qing |
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| Affiliation: | 1;2;1.School of Management;Dalian University of Technology;Dalian 116024;2.Department of Mathematics;Anshan Normal University;Anshan 114005 |
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| Abstract: | The main defect of traditional methods of FCM algorithm is sensitive to the isolated data and is to know the number of clustering in advance.A fuzzy clustering algorithm NSFCM is presented in this paper,and NSFCM agorithm is applied to text mining.This algorithm adds a weight to the membership of the data,which is to decrease the effect on the initial cluster center.This paper applies average information entropy to find the number of clusters and adopts a density function algorithm to find the initial clust... |
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| Keywords: | number of clustering text clustering fuzzy clustering |
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