A Semantic Relevancy Measure Algorithm of Chinese Sentences
The semantic relevancy measures between sentences play an increasingly important role in text-related research and applications in areas such as text categorization, text-reasoning, text structure analysis and Question-Answering system. In this paper, focusing on the Chinese short text, a novel semantic relevancy measure algorithm between sentences is proposed. This method calculates sentence relevancy by combining the word-form feature, semantic feature and syntax feature in sentences. Besides semantic feature, the syntax structure information of sentences is also considered. Experiments prove that the proposed algorithm is efficient and useful in semantic relevancy measure of Chinese sentence.
KeywordsSemantic Relevancy Syntax Feature Semantic Dependency Grammar Multi-feature Combination
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