文献类型：期刊文献

英文题名：Concept vector for semantic similarity and relatedness based on WordNet structure

作者：Liu, Hongzhe[1,2]; Bao, Hong[1,2]; Xu, De[1]

第一作者：刘宏哲;Liu, Hongzhe

通讯作者：Liu, H.

机构：[1] Beijing Jiaotong University, Beijing, China; [2] Beijing Union University, Beijing Key Laboratory of Information Service Engineering, Beijing, China

第一机构：Beijing Jiaotong University, Beijing, China

年份：2012

卷号：85

期号：2

起止页码：370-381

外文期刊名：Journal of Systems and Software

收录：EI(收录号：20115214644226)

基金：This project was supported by the project supported by Beijing Municipal Commission of Education (Grant No. KM201111417002 ), Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality (Grant No. PHR201108419 ) and (Grant No. PHR 200907120 ), the National Natural Science Foundation of China (Grant No. 60972045 ).

语种：英文

外文关键词：Forestry - Semantics - Ontology - Trees (mathematics)

摘要：We define WordNet based hierarchy concept tree (HCT) and hierarchy concept graph (HCG), HCT contains hyponym/hypernym kind of relation in WordNet while HCG has more meronym/holonym kind of edges than in HCT, and present an advanced concept vector model for generalizing standard representations of concept similarity in terms of WordNet-based HCT. In this model, each concept node in the hierarchical tree has ancestor and descendent concept nodes composing its relevancy nodes, thus a concept node is represented as a concept vector according to its relevancy nodes' local density and the similarity of the two concepts is obtained by computing the cosine similarity of their vectors. In addition, the model is adjustable in terms of multiple descendent concept nodes. This paper also provides a method by which this concept vector may be applied with regard to HCG into HCT. With this model, semantic similarity and relatedness are computed based on HCT and HCG. The model contains structural information inherent to and hidden in the HCT and HCG. Our experiments showed that this model compares favorably to others and is flexible in that it can make comparisons between any two concepts in a WordNet-like structure without relying on any additional dictionary or corpus information. ? 2011 Elsevier Inc.