Sentence Semantic Similarity Calculation Based on Multi-feature Fusion

The traditional sentence semantic similarity computing approaches usually only focus on one feature of a sentence and result in imbalance between the recall and the accuracy.Therefore,this paper describes a method for semantic similarity computation based on the Multi-feature of a Sentence(MFS).It is integrating more features of the weights of words,word semantics and sentence structure.The result of experiment show that compared with Jaccard coefficient method,the MFS method increased for comprehensive index F-measure.In a case-based question answering system the MRR value of the presented method is higher than other compared methods.