Semantic similarity of short texts in languages with a deficient natural language processing support


Measuring the semantic similarity of short texts is a noteworthy problem since short texts are widely used on the Internet, in the form of product descriptions or captions, image and webpage tags, news headlines, etc. This paper describes a methodology which can be used to create a software system capable of determining the semantic similarity of two given short texts. The proposed LInSTSS approach is particularly suitable for application in situations when no large, publicly available, electronic linguistic resources can be found for the desired language. We describe the basic working principles of the system architecture we propose, as well as the stages of its construction and use. Also, we explain the procedure used to generate a paraphrase corpus which is then utilized in the evaluation process. Finally, we analyze the evaluation results obtained from a system created for the Serbian language, and we discuss possible improvements which would increase system accuracy.

Decision Support Systems, Vol. 55, No. 3, pp. 710-719, Elsevier