by Haisheng Li, Yun Tian, Qiang Cai
Abstract:
Traditional methods to modeling semantic similarity only compute the common characteristics and uncommon characteristics, without considering the structural relationship between concepts. In this paper, a new semantic similarity method based on information content is proposed. It evolves from feature model, the function $\lambda$ in the algorithm which defines the relative importance of the uncommon characteristics, depends on the hierarchy in WordNet. In addition, the information content measure also relies on WordNet. Experiments show that, comparing the conventional two similarity measures Resnik and Lin, the proposed method gets more reasonable results with human judgments.
Reference:
Improvement of semantic similarity algorithm based on WordNet (Haisheng Li, Yun Tian, Qiang Cai), In Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on, IEEE, 2011.
Bibtex Entry:
@inproceedings{Li2011a,
abstract = {Traditional methods to modeling semantic similarity only compute the common characteristics and uncommon characteristics, without considering the structural relationship between concepts. In this paper, a new semantic similarity method based on information content is proposed. It evolves from feature model, the function $\lambda$ in the algorithm which defines the relative importance of the uncommon characteristics, depends on the hierarchy in WordNet. In addition, the information content measure also relies on WordNet. Experiments show that, comparing the conventional two similarity measures Resnik and Lin, the proposed method gets more reasonable results with human judgments.},
author = {Li, Haisheng and Tian, Yun and Cai, Qiang},
booktitle = {Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on},
isbn = {9781424487561},
keywords = {- semantic similarity,SML-LIB-BIBLIO,information content,lang:ENG,wordnet},
mendeley-tags = {SML-LIB-BIBLIO,lang:ENG},
pages = {564--567},
publisher = {IEEE},
title = {{Improvement of semantic similarity algorithm based on WordNet}},
url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=5975649},
year = {2011}
}