Topic segmentation of news speech using word similarity
Topic segmentation of news speech using word similarity
复制标题
利用词相似度进行新闻语音主题分割
DOI：
10.1145/354384.376354
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发表时间：
2000
期刊：
影响因子：
--
通讯作者：
Y. Ariki
中科院分区：
文献类型：
--
作者：
S. Takao;J. Ogata;Y. Ariki
传统的主题分割采用余弦度量作为连续段落之间的相似度。然而，余弦度量存在一个问题，即除非文章中包含完全相同的单词，否则它不能反映相似度。针对这一问题，本文提出了一种通过收集相同主题段的方法，直接从输入数据中自动获取不同词之间的词相似度。在此基础上，提出了一种基于词相似度的文本相似度计算方法。最后，提出了一种无监督模式下基于段落相似度的主题分割方法。
Conventional topic segmentation utilizes cosine measure as the similarity between consecutive passages. However, the cosine measure has a problem that it can not reflect the similarity unless exactly the same words are included in the passages. To solve this problem, in this paper, we propose a method to acquire the word similarity between different words from the input data directly and automatically by managing to collect the same topic sections. Further more, we propose a method to compute the passage similarity based on the word similarity. Finally we propose a method of topic segmentation based on the passage similarity in an unsupervised mode.