Short Text Similarity Measure Based on Double Vector Space Model

Short text similarity measure is the basis of classification and duplicate checking of the short texts. Allowing for the insufficient consideration of the sentence semantic and structure information in similarity calculation between two short texts, we propose a novel method of short text similarity calculation based on double vector space model on the basis of traditional vector space model. Creatively transforming traditional vector space model into double vector space model. We utilize the numeral data link relations of Wikipedia to calculate semantic similarity between words, and calculate text structure similarity by dependency trees. Finally, we get the synthetic similarity by combining the semantic similar vector and structure similar vector. Our experiment results demonstrate that the proposed method has higher accuracy than other methods.