| 基于自适应聚类的文本潜在主题的自动发现 |
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| 引用本文： | 胡珀,何婷婷.基于自适应聚类的文本潜在主题的自动发现[J].郑州大学学报(理学版),2007,39(2):92-95. |
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| 作者姓名： | 胡珀 何婷婷 |
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| 作者单位： | 华中师范大学计算机科学系,武汉,430079 |
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| 基金项目： | 国家自然科学基金;国家社会科学基金 |
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| 摘 要： | 提出了一种自适应于不同题材文本自动确定其包含的潜在主题数K的方法.考虑到大多数文本的潜在主题分布符合段落密度特性,提出以段落为中心的研究策略,通过采用基于K均值的聚类算法联同自定义判别函数的聚类分析方法,实现了段落自适应聚类下的文本潜在主题的自动发现.实验结果表明,该方法在一定程度上能有效处理普遍存在的文风自由且主题表达灵活多样的各式文本.
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| 关 键 词： | 自然语言处理 主题发现 聚类 |
| 文章编号： | 1671-6841(2007)02-0092-04 |
| 修稿时间： | 11 15 2006 12:00AM |
Latent Topic Discovery from Text Based on Adaptive Clustering Algorithm |
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| HU Po,HE Ting-ting.Latent Topic Discovery from Text Based on Adaptive Clustering Algorithm[J].Journal of Zhengzhou University:Natural Science Edition,2007,39(2):92-95. |
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| Authors: | HU Po HE Ting-ting |
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| Institution: | Department of Computer Science, Huazhong Normal University, Wuhan 430079, China |
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| Abstract: | A novel approach to discovering topics and determining the number of latent topics K in a text automatically is proposed.By adopting K-means clustering algorithm as well as a clustering analysis algorithm based on self-defined discriminative function,the number of different latent topics in a text is captured and the diverse topics are found accordingly.Experimental results demonstrate that the proposed approach can deal with various texts with free writing style and flexible topic distribution effectively. |
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| Keywords: | natural language processing topic discovery clustering |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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