Computer Science ›› 2020, Vol. 47 ›› Issue (8): 164-170.doi: 10.11896/jsjkx.190600153

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Opinion Word-pairs Collaborative Extraction Based on Dependency Relation Analysis

ZHAO Wei1, 2, LIN Yu-ming1, WANG Chao-qiang1, CAI Guo-yong1   

  1. 1 Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China
    2 School of Data Science & Engineering, East China Normal University, Shanghai 200062, China
  • Online:2020-08-15 Published:2020-08-10
  • About author:ZHAO Wei, born in 1995, postgraduate.His main research interests include opinion mining and so on.
    LIN Yu-ming, born in 1978, Ph.D, professor.His main research interests include opinion mining, knowledge graph, and massive data management.
  • Supported by:
    This work was supported by the Guangxi Natural Science Foundation (2018GXNSFDA281049), National Natural Science Foundation of China (61662015, U1711263), Science and Technology Major Project of Guangxi Province (AA19046004) and Innovation Project of Guet Graduate Education (2018YJCX48) and Project of Guangxi Key Laboratory of Trusted Software(kx201916).

Abstract: In the same category of commodities, opinion word-pairs usually have strong opinion dependence relation to the opinion targets and the opinion words contained in them.Therefore, in the extraction process of opinion word-pairs, they can be extracted by analyzing the opinion dependence relations among the words in the review sentences.Firstly, a dependency relation analysis model is constructed to obtain the dependency relation information of each word in a review sentence, and the basic model is defined as LSTM neural network.Secondly, it is assumed that one of the item that opinion word-pairs contained in review sentence is known, and the known item is used as the model’s attention information, so that the model can focus on extracting the words of phrases associated with the known item with strong opinion dependence from the review sentence as another unknown item in the opinion word-pairs.Finally, the word-pairs with the highest score of the opinion dependence relation are output as the opinion word-pairs.Then a compound model is designed to realize the mining of opinion word pairs without knowing the known items in advance by combining the two models which contain the information of different known items in the opinion word-pairs.

Key words: Attention mechanism, Neural network, Opinion dependency relation analysis, Opinion pair

CLC Number: 

  • TP391
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