Computer Science ›› 2018, Vol. 45 ›› Issue (1): 67-72.doi: 10.11896/j.issn.1002-137X.2018.01.010

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Entity Hyponymy Acquisition and Organization Combining Word Embedding and Bootstrapping in Special Domain

MA Xiao-jun, GUO Jian-yi, XIAN Yan-tuan, MAO Cun-li, YAN Xin and YU Zheng-tao   

  • Online:2018-01-15 Published:2018-11-13

Abstract: The semantic relation of entity hypomypy is important to build the domain knowledge graphs.The organization of hierarchical relations is not considered in the traditional method of extracting hyponymy.A method of extracting and organizing the entity hyponymy in the specific field was proposed in this paper,which combines the word embedding and bootstrapping method.Firstly,the tourism corpus is selected as seed corpus,then the hyponymy patterns included in the seed corpus are clustered based on the method of word embedding similarity.Thus,the patterns of high-confidence level are filtrated which is used to identify hyponymy in the unlabeled corpus.After that,the high-confidence instances of relation are obtained which are selected to put in the seed sets.And the next iteration is performed until all the instances of relation are obtained.Finally,the mapping learning methods are applied to conduct the hierarchical relation of domain entity based on the character of the entity of domain hierarchical relations and the vector-deviation of the hyponymy pairs of the entity.The experimental results show that the proposed method improves the F-value by 10% compared with the traditional method.

Key words: Hyponymy relation,Relation extraction,Bootstrapping method,Word embedding,Projection learning,Hierarchical relation organization

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