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Princeton WordNet (PWN) is a lexicon-semantic network based on cognitivelinguistics, which promotes the development of natural language processing.Based on PWN, five Chinese wordnets have been developed to solve the problemsof syntax and semantics. They include: Northeastern University Chinese WordNet(NEW), Sinica Bilingual Ontological WordNet (BOW), Southeast University ChineseWordNet (SEW), Taiwan University Chinese WordNet (CWN), Chinese Open WordNet(COW). By using them, we found that these word networks have low accuracy andcoverage, and cannot completely portray the semantic network of PWN. So wedecided to make a new Chinese wordnet called Multi-Fusion Chinese Wordnet (MCW)to make up those shortcomings. The key idea is to extend the SEW with the helpof Oxford bilingual dictionary and Xinhua bilingual dictionary, and thencorrect it. More specifically, we used machine learning and manual adjustmentin our corrections. Two standards were formulated to help our work. Weconducted experiments on three tasks including relatedness calculation, wordsimilarity and word sense disambiguation for the comparison of lemma'saccuracy, at the same time, coverage also was compared. The results indicatethat MCW can benefit from coverage and accuracy via our method. However, itstill has room for improvement, especially with lemmas. In the future, we willcontinue to enhance the accuracy of MCW and expand the concepts in it.

Multi-Fusion Chinese WordNet (MCW) : Compound of Machine Learning and Manual Correction