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Parse Tree-based SAO Structure Identification
Received date: 2016-08-25
Revised date: 2016-10-16
Online published: 2016-11-05
[Purpose/significance] Subject-Action-Object (SAO) is a triple structure which can be used to both describe topics in details and explore the relationship between topics. SAO analysis is a fast-growing research field. In order to obtain the SAO structures which are suitable for the bibliometric analysis, three problems need to be solved. Recall and precision have been low. The SAOs don't have close relationships with domain topics. There is a problem of matrix sparsity. [Method/process] This paper proposed a parse tree-based SAO identification method for the bibliometric analysis. It included:(1) a model to identify the core components of SAO structures, where co-word analysis and term clumping processes were involved; (2) a parse tree-based hierarchical SAO extraction model to implement SAO structures identification. [Result/conclusion] The case study shows that the average precision and average recall of the proposed method is 0.8058 and 0.8446. The SAO extracted with our method has a great relationship with the domain topic and improves the matrix sparsity, which makes it be used as an effective tool for the bibliometric analysis.
Yang Chao , Zhu Donghua , Heng Xiaofan , Wang Xuefeng . Parse Tree-based SAO Structure Identification[J]. Library and Information Service, 2016 , 60(21) : 113 -121 . DOI: 10.13266/j.issn.0252-3116.2016.21.015
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