An English-Chinese Cross-lingual Word Semantic Similarity Measure Exploring Attributes and Relations

Word semantic similarity measuring is a fundamental issue to many NLP applications and the globalization has made an urgent request for cross-lingual word similarity measure. This paper proposed a word semantic similarity measure which is able to work in cross-lingual scenarios. Basically, a concept can be defined by a set of attributes. The basic idea of this work is to compute the similarity between words by exploring their attributes and relations. For a given word pair, we first compute similarities between their attributes by combining distance, depth and relation information. Then word similarity are computed through a combination scheme. The algorithm is implemented based on an English-Chinese bilingual ontology HowNet. Experiments show that the proposed algorithm results in high correlation against human judgments, which encourages its broad application in cross-lingual applications.