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1. HLDA BASED SENTENCE SCORING FOR MULTI-DOCUMENT SUMMARY | |||
LI Lei,YU Jia | |||
Computer Science and Technology 22 October 2013 | |||
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Abstract:In recent years, the multi-document summary technology has gotten more and more attention in the field of natural language processing. However, the relationship between the topics and the level information are rarely considered, and sentence scoring is also a very important and difficult task in the multi-document summary process. The results of hLDA (hierarchical Latent Dirichlet Allocation) in the hierarchical topic modeling have been widely validated. Therefore this paper focused on the nodes in the hLDA model, researched the hLDA and semantic based sentence scoring method and presented seven algorithms to provide a strong basis for the multi-document summary. | |||
TO cite this article:LI Lei,YU Jia. HLDA BASED SENTENCE SCORING FOR MULTI-DOCUMENT SUMMARY[OL].[22 October 2013] http://en.paper.edu.cn/en_releasepaper/content/4565453 |
2. News Sentiment Classification for Chinese Document Based on Semantic Orientation | |||
SHI Zhenliang | |||
Computer Science and Technology 06 May 2011 | |||
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Abstract:Sentiment classification is a way to analyze the subjective information in the text and then mine the opinion. In this paper, we focus on the news sentiment classification based on Chinese document-level. On the systematically analyzing the importance and difficulties of the news sentiment classification, this paper proposes an improved sentiment classification approach for Chinese document based on semantic orientation. The approach has four steps: (1) the news documents are pre-processed; (2) the sentiment words and the negative words are integrated processed; (3) the topic words and the sentiment words are integrated processed; (4) the weight is calculated based on a sentiment word dictionary and the context information. The experimental results show that our improved method can achieve better performance in Chinese document level sentiment classification. | |||
TO cite this article:SHI Zhenliang. News Sentiment Classification for Chinese Document Based on Semantic Orientation[OL].[ 6 May 2011] http://en.paper.edu.cn/en_releasepaper/content/4423193 |
3. The Method of Analyzing Affective Tendency in Text | |||
Song Guangpeng | |||
Computer Science and Technology 12 November 2007 | |||
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Abstract:This paper introduces a method targeted at analyzing affective tendency of Chinese texts. First of all, Chinese texts are processed, and then affective words in texts are tagged with the affective words dictionary, and then sentence structure are analyzed. Affective values of the various elements of the sentences have different affective effect to the affective values of sentences; hence all affective elements for the affective values of sentences should be analyzed and weighted. The affective dictionary is based on psychology model, each word has two affective dimensions: activation value, pleasure value. Each word in every dimension has a corresponding value. The affective value of the text is two-dimensional. An affective tendency analyze system targeted at Chinese texts is realized, which consists of a Chinese processing engine and an affective analyzing engine. The affective tendency engine includes affective words identification function, and a rule set of sentences structure. Tests were carried out by using the affective texts. | |||
TO cite this article:Song Guangpeng. The Method of Analyzing Affective Tendency in Text[OL].[12 November 2007] http://en.paper.edu.cn/en_releasepaper/content/16297 |
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