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A Concept-Based Knowledge Representation Model for Semantic Entailment Inference
Zhao MJ(赵美静); Ni WC(倪晚成); Zhang HD(张海东); Yang YP(杨一平); Ni WC(倪晚成)
2014
会议名称Proceedings of 33rd Control Conference (CCC),Chinese, 2014
会议录名称Proceedings of 33rd Control Conference (CCC),Chinese, 2014
页码522 - 527
会议日期2014,0728-0730
会议地点南京
摘要Semantic entailment is a fundamental problem in natural language understanding that has a large number of applica-tions. Knowledge acquisition and knowledge representation are usually the crucial parts in semantic inference strategy. This paper presents a principled approach to semantic entailment problem that builds on a concept-based knowledge representation model (CKR). This model formally defines the concept as a triple (attribute, relation and behavior) and the knowledge of a concept can be illustrated with the triple. We propose a semantic inference strategy that against identify text segments which dissimilar on their surface form but share a common meaning. The inference strategy avoids syntactic analysis steps. A prelim-inary evaluation on the PASCAL text collection is presented. Experimental results show that our concept-based inference strat-egy is effective and has strong potential space.
关键词Semantic Inference Knowledge Representation Concept Ckr Semantic Entailment
收录类别EI
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/11215
专题综合信息系统研究中心
通讯作者Ni WC(倪晚成)
作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Zhao MJ,Ni WC,Zhang HD,et al. A Concept-Based Knowledge Representation Model for Semantic Entailment Inference[C],2014:522 - 527.
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