[Objective] This article aims to extract concept attribute instances in innovation sentences, and then to explore the relationship between concepts. [Methods] A method of recognizing core concept and concept attribute instances from dependency tree is presented. This method is based on the results of semantic role labeling and dependency parsing, and takes advantage of property of classes in domain Ontology. Considering the feature of dependency parsing, a concept combination module and a conjunction relationship detection module are designed to improve the effect of concept attribute instances recognition. [Results] The results show that the F value of core concept recognition is 77.94%, and the average F value of concept attribute instances recognition is around 90%. [Limitations] Stanford parsing tool leads to wrong parsing results which may result in inaccurate recognition. The class of Properties or Attributes in NCIt is not well filtered and standardized. [Conclusions] This method can effectively extract core concepts and concept attribute instances in innovation sentences.
张帆, 乐小虬. 领域科技文献创新点句中主题属性实例识别方法研究[J]. 现代图书情报技术, 2015, 31(5): 15-23.
Zhang Fan, Le Xiaoqiu. Research on Recognition of Concept Attribute Instances in Innovation Sentences of Scientific Research Paper. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2015.05.03.
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