随着在线网页的指数型增长,自动摘要技术越来越受到人们的关注。针对抽取型摘要很少对文本进行语义分析、抽取出的句子可能偏离主题等缺陷,结合单文本摘要的特点,提出了一种英文自动摘要方法TLETS(TF-ISF and LexRank based English Tex...随着在线网页的指数型增长,自动摘要技术越来越受到人们的关注。针对抽取型摘要很少对文本进行语义分析、抽取出的句子可能偏离主题等缺陷,结合单文本摘要的特点,提出了一种英文自动摘要方法TLETS(TF-ISF and LexRank based English Text Summarization)。该方法采用WordNet对向量空间模型的特征词进行概念统计,计算每个概念词的TF-ISF值作为其权值,最后计算每个句子的LexRank权值并提取出权值最高的几个句子作为摘要。实验结果表明,TLETS方法能很好地得到摘要结果。展开更多
Following the expanding of VSM and LSI, a text classification based on Concept Space is proposed in thispaper. Information gaining is applied to acquire concepts based on large training set. Concept Space is built by ...Following the expanding of VSM and LSI, a text classification based on Concept Space is proposed in thispaper. Information gaining is applied to acquire concepts based on large training set. Concept Space is built by acquir-ing latent semantic indexing data, building a latent semantic space by LSI, and then adding the class-basis vector. Thecalculating method of the word-similarity, the text-similarity, the similarity of the text vector and the class-basis vec-tor in Concept Space are presented. Experiment results show the Concept Space method is superior to Vector SpaceModel. This paper also discusses the future work the problem of concept space learning.展开更多
文摘随着在线网页的指数型增长,自动摘要技术越来越受到人们的关注。针对抽取型摘要很少对文本进行语义分析、抽取出的句子可能偏离主题等缺陷,结合单文本摘要的特点,提出了一种英文自动摘要方法TLETS(TF-ISF and LexRank based English Text Summarization)。该方法采用WordNet对向量空间模型的特征词进行概念统计,计算每个概念词的TF-ISF值作为其权值,最后计算每个句子的LexRank权值并提取出权值最高的几个句子作为摘要。实验结果表明,TLETS方法能很好地得到摘要结果。
文摘Following the expanding of VSM and LSI, a text classification based on Concept Space is proposed in thispaper. Information gaining is applied to acquire concepts based on large training set. Concept Space is built by acquir-ing latent semantic indexing data, building a latent semantic space by LSI, and then adding the class-basis vector. Thecalculating method of the word-similarity, the text-similarity, the similarity of the text vector and the class-basis vec-tor in Concept Space are presented. Experiment results show the Concept Space method is superior to Vector SpaceModel. This paper also discusses the future work the problem of concept space learning.
