Quantifying semantic similarity of Chinese wordsfrom HowNet

Semantic similarity is a fundamental concept and widely researched and used in the fields of natural language processing. However, methodologies for measuring semantic similarity are language-dependent This paper presents a system similarity based measure of semantic similarity for Chinese words from HowNet, an online bilingual (Chinese-English) common sense ontology. The measure is determined in three steps: First, a sememe network is built from concept feature files of HowNet for preparation,, then semantic similarity degree between sememes are given by quantifying their semantic paths in the sememe network, and sememe weighting method is also provided, after that, a system similarity based semantic similarity degree between Chinese words is presented to combine these elements into a single measure. The experimental results have been adopted by the Chinese query matching system whose precision and flexibility are enhanced thereby.