yiGou: A Semantic Text Similarity Computing System Based on SVM
نویسندگان
چکیده
This paper describes the yiGou system we developed to compute the semantic similarity of two English sentences, which we submitted to the SemEval 2015 Task 2 (English subtask). The system uses a support vector machine model with literal similarity, shallow syntactic similarity, WordNet-based similarity and latent semantic similarity to predict the semantic similarity score of two short texts. In our experiments, WordNet-based and LSA-based features performed better than other features. Out of the 73 submitted runs, our two runs ranked 38 and 42, with mean Pearson correlation 0.7114 and 0.6964 respectively.
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