Concept Vector for Similarity Measurement Based on Hierarchical Domain Structure

Authors

  • Hong Zhe Liu
  • Hong Bao
  • De Xu

Keywords:

Concept similarity, concept vector model, cosine similarity measure, hierarchical taxonomy

Abstract

The concept vector model generalizes standard representations of similarity concept in terms of tree-like structure. In the 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' density and the similarity of the two concepts is obtained by computing cosine similarity between their vectors. In addition, the model is adjusted in terms of local density and multiple descendents problem. The model contains structure information inherent and hidden in the tree. We show that this measure compares favorably to other measures, and it is flexible in that it can make comparisons between any two concepts in a hierarchical tree without relying on additional dictionary or corpus information.

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Author Biographies

Hong Zhe Liu

Beijing Jiaotong University
Beijing Union University
Beijing, China

Hong Bao

Beijing Jiaotong University
Beijing Union University
Beijing, China

De Xu

Beijing Jiaotong University
Beijing, China

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Published

2012-01-26

How to Cite

Liu, H. Z., Bao, H., & Xu, D. (2012). Concept Vector for Similarity Measurement Based on Hierarchical Domain Structure. COMPUTING AND INFORMATICS, 30(5), 881–900. Retrieved from http://www.cai.sk/ojs/index.php/cai/article/view/201