Computer Science ›› 2017, Vol. 44 ›› Issue (5): 280-284.doi: 10.11896/j.issn.1002-137X.2017.05.051

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Word Semantic Relevancy Computation and Categories Identification Based on Chinese Compound Sentences

YANG Jin-cai, CHEN Zhong-zhong, SHEN Xian-jun and HU Jin-zhu   

  • Online:2018-11-13 Published:2018-11-13

Abstract: As a critical technique in the field of Chinese information processing,word semantic relevancy computation plays an important role in information retrieval,ambiguity elimination,and text processing.Using syntactic theory and the collocation theory of the relation markers of Chinese compound sentences,as well as making the corpus of Chinese compound sentences and some compound sentences from search engine as the data resource,a semantic relevancy computation method was proposed based on Chinese compound sentence (SRCCS).This method can not only compute the word semantic relevancy,but also show the property and category of the word semantic relevancy.Compared with the method of short text semantic relevancy,this method chooses a smaller scope of evaluation objects,so the results are more accurate and have little computational complexity.Compared with the result by Google Distance,the new measure is more reliable and effective.

Key words: Complex sentences,Semantic relevancy,Relations marker,Relations category

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