| 一种基于模糊加权的改进文本聚类方法 |
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| 引用本文： | 刘海峰,姚泽清,刘守生. 一种基于模糊加权的改进文本聚类方法[J]. 微电子学与计算机, 2011, 28(9): 39-42 |
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| 作者姓名： | 刘海峰 姚泽清 刘守生 |
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| 作者单位： | 解放军理工大学理学院,江苏南京,210007 |
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| 基金项目： | 国家自然科学基金项目(71071161) |
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| 摘 要： | 首先提出了一种优化初始中心点方法用以解决聚类的局部最优问题.同时通过样本的模糊加权减少边缘噪音数据对聚类效率的影响.文本聚类试验表明,该模糊文本聚类算法取得较好的聚类效果.
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| 关 键 词： | k-means算法 模糊聚类 文本聚类 模糊加权 |
An Improved Text Clustering Method Based on Fuzzy Weighting |
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| LIU Hai-feng,YAO Ze-qing,LIU Shou-sheng. An Improved Text Clustering Method Based on Fuzzy Weighting[J]. Microelectronics & Computer, 2011, 28(9): 39-42 |
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| Authors: | LIU Hai-feng YAO Ze-qing LIU Shou-sheng |
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| Affiliation: | LIU Hai-feng,YAO Ze-qing,LIU Shou-sheng(Institute of Sciences,PLA University of Science and Technology,Nanjing 210007,China) |
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| Abstract: | This paper proposes a new way that selects initial cluster center in order to solve the partially most superior phenomenon.By using the fuzzy weighting on the samples,this improved method decreases the influence that the k-means algorithm is very sensitive to the isolated point.Lastly,we have a test about text clustering and the result shows that this method obtains good clustering effect. |
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| Keywords: | k-means algorithm fuzzy clustering text clustering fuzzy weighting |
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