Abstract

This paper describes our submission for the* SEM shared task of Semantic Textual Similarity. We estimate the semantic similarity between two sentences using regression models with features: 1) n-gram hit rates (lexical matches) between sentences, 2) lexical semantic similarity between non-matching words, 3) string similarity metrics, 4) affective content similarity and 5) sentence length. Domain adaptation is applied in the form of independent models and a model selection strategy achieving a mean correlation of 0.47.

Date

2013

Authors

Nikolaos Malandrakis, Elias Iosif, Vassiliki Prokopi, Alexandros Potamianos, Shrikanth Narayanan

Conference

Second Joint Conference on Lexical and Computational Semantics (* SEM), Volume 1: Proceedings of the Main Conference and the Shared Task: Semantic Textual Similarity

Pages

103-108