Research on Topic Extraction from Uighur Comment Text
Huang Jun · Zhongwen xinxi xuebao · 2013
Topic extraction is one of the core tasks of opinion mining.This paper proposes a claim-level topic extraction method,which aims at extracting explicit topics and implicit topics of Uighur comment texts.This method uses GLR-Cascaded LDA(Cascaded LDA model for global topic,local topic and the relation between them,GLR-Cascaded LDA) to extract the local topics of paragraph level,global topics of document level,establish the global-local topic relationship,and corresponds the relationships to each opinion claim.It adopts Bootstrapping and pattern matching to extract the topics of explicit claims.Finally,the implicit topic inference algorithm is applied to deduce the topics of implicit claims.The ultimate goal of topic extraction is to establish an opinion quadruple of claim-topic OC,GT,LT,LT for each opinion claim.Experimental results indicate the effectiveness of the proposed method in topic extraction task.