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基于情感主题的博客性别分类模型

发表时间:2013-08-31  浏览量:1312  下载量:496
全部作者: 王昊,杨亮,林鸿飞
作者单位: 大连理工大学计算机科学与技术学院
摘 要: 提出基于情感的博客分类模型,通过情感主题分析解决博客性别分类问题。模型首先给出一种基于潜在狄利克雷分布(latent Dirichlet allocation, LDA)的情感词扩展方法;其次利用WordNet-Affect的情感词及扩展的情感词,通过LDA模型给出了男性和女性的情感主题并提出筛选情感主题的方法,得到更有性别区分度的情感主题;最后,通过情感主题与内部词典给出模型的性别计算公式。实验表明,情感主题有助于提升博客性别分类结果。
关 键 词: 自然语言处理;博客性别分类;情感主题;潜在狄利克雷分布模型
Title: A blog gender classification model based on sentiment topic
Author: WANG Hao, YANG Liang, LIN Hongfei
Organization: School of Computer Science and Technology, Dalian University of Technology
Abstract: This paper provided a blog gender classification model based on sentiment topic. Firstly, the model provided a sentiment extension method based on latent Dirichlet allocation (LDA). Then, sentiment topics of men and women were proposed using WordNet-Affect sentiment extension, and a selecting method was also proposed to get the useful topic through LDA. At last, the blog gender classification model was provided by mixing sentiment topic and inside dictionary. The experiment results showed that sentiment topic was useful to advance the blog gender classification result.
Key words: natrual language processing; blog gender classification; sentiment topic; latent Dirichlet allocation model
发表期数: 2013年8月第16期
引用格式: 王昊,杨亮,林鸿飞. 基于情感主题的博客性别分类模型[J]. 中国科技论文在线精品论文,2013,6(16):1542-1549.
 
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