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Extracting Book Review Topics with Knowledge Base |
Ruihua Qi1,2( ),Junyi Zhou1,2,Xu Guo2,Caihong Liu2 |
1(Linguistics Research Center, Dalian University of Foreign Languages, Dalian 116044, China) 2(Research Center for Multilingual Big Data in Cyberspace, Dalian University of Foreign Languages, Dalian 116044, China) |
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Abstract [Objective] This paper tries to extract topics from book reviews with the help of natural language semantics. [Methods] We proposed a method to retrieve the explicit and implicit topic keywords with the global semantic information from common sense knowledge base. [Results] The sentence coverage rate with the knowledge base method and the lexical diversity of the proposed method were 30.8% and 0.36% higher than those of the Double-Propagation algorithm. Then, based on the extracted topic words, we created a cluster map to identify the topic keywords identified by the nodes cluster centrality. [Limitations] There is no domain knowledge base in the field of book reviews. [Conclusions] The proposed method based on Knowledge Base improves the sentence coverage and lexical diversity of topics extracted from book reviews.
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Received: 10 August 2018
Published: 15 August 2019
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