An acquisition method of domain-specific terminological hyponym based on structure features of sentence
Wang Changyo · Journal of Chongqing University of Posts and Telecommunications · 2014
Aimed at the difficulty of obtaining the hyponymy relations of concept in the construction of domain ontology,a method based on the structure features of sentence for domain-specific terminological hyponymy extraction is proposed.Firstly,the CCRFs(cascaded conditional random fields) algorithm is used to recognize the entity of hyponymy. Secondly,by analyzing the sentence structure characteristic,the sentence structure feature fusing concept hyponymy is obtained. Finally,a method based on SVM(support vector machine) with the structure features of sentence is used to extract the hyponymy relations of domain- specific terminological. In order to verify the effectiveness of the proposed method,some tests are given to gain hyponymy entity relations of the tourism concept. Experiments results show that the value F of the classifier based on CCRFs is bigger than that of the classifier based on CRFs(Conditional Random Fields) by 6. 57 percent and the value F of the hyponymy extraction method based on SVM with the structure features of sentence is bigger than that of the method based on CRFs(conditional random fields) by 4. 68 percent. It is obvious that the proposed method in this paper is more effective than the existing methods.