%A ZHAO Wei, LIN Yu-ming, WANG Chao-qiang, CAI Guo-yong %T Opinion Word-pairs Collaborative Extraction Based on Dependency Relation Analysis %0 Journal Article %D 2020 %J Computer Science %R 10.11896/jsjkx.190600153 %P 164-170 %V 47 %N 8 %U {https://www.jsjkx.com/CN/abstract/article_19308.shtml} %8 2020-08-15 %X 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.