Entity relevance based on the area subgraph

Chen Chen*, Hui Lin Liu, Jun Chang Xin, Guo Ren Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

A new method for the measurement of entity relevance was proposed on the basis of entity relationship graph. By defining the area graph, the semantic of each entity was well presented. To speed up the calculation of the similarity between two area subgraphs, the area subgraphs were first converted into semantic trees. Then the kernel function was used to calculate the similarity by counting the number of shared subtrees. At last, the proposed methods were evaluated on the basis of the experimental results. The experimental results proved that the proposed method had a good performance in both accuracy and efficiency.

Original languageEnglish
Pages (from-to)1551-1554
Number of pages4
JournalDongbei Daxue Xuebao/Journal of Northeastern University
Volume33
Issue number11
Publication statusPublished - Nov 2012
Externally publishedYes

Keywords

  • Area subgraph
  • Entity
  • Entity relevance
  • Semantic tree
  • Tree kernel

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