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Blog Opinion Retrieval with Generation Model and Mixture Model
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作者 Jie Chen Zhendong Niu +1 位作者 Xi Li Lizhe Song 《Journal of Beijing Institute of Technology》 EI CAS 2017年第3期396-403,共8页
Blog opinion retrieval aims to find blogs with opinionated information related to a given topic.Its main problem is to compute the opinion score,which balances topic relevance and opinion relevance.To deal with this p... Blog opinion retrieval aims to find blogs with opinionated information related to a given topic.Its main problem is to compute the opinion score,which balances topic relevance and opinion relevance.To deal with this problem a generative model deduced by a Bayesian approach is pro-posed,and an improved mixture model is proposed to estimate the opinion relevance between a blog and a given topic in our retrieval framework.Moreover,pointwise mutual information is used to expand sentiment words for different topics based on a general sentimental lexicon.The correlation between topic and candidate words is applied in the process of both expanding sentiment words and estimating sentence opinion scores.Experimental results show that the proposed approaches improve upon the state-of-the-art opinion retrieval method on TREC2010 dataset. 展开更多
关键词 blog opinion retrieval opinion mining blog site search hybrid model
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