Title: A Novel Comprehensive Approach for Estimating Concept Semantic Similarity in WordNet,
Abstract: Computation of semantic similarity between concepts is an important
foundation for many research works. This paper focuses on IC computing methods
and IC measures, which estimate the semantic similarities between concepts by
exploiting the topological parameters of the taxonomy. Based on analyzing
representative IC computing methods and typical semantic similarity measures,
we propose a new hybrid IC computing method. Through adopting the parameter
dhyp and lch, we utilize the new IC computing method and propose a novel
comprehensive measure of semantic similarity between concepts. An experiment
based on WordNet "is a" taxonomy has been designed to test representative
measures and our measure on benchmark dataset R&G, and the results show that
our measure can obviously improve the similarity accuracy. We evaluate the
proposed approach by comparing the correlation coefficients between five
measures and the artificial data. The results show that our proposal
outperforms the previous measures.