Paper: DeepPurple: Lexical, String and Affective Feature Fusion for Sentence-Level Semantic Similarity Estimation

ACL ID S13-1014
Title DeepPurple: Lexical, String and Affective Feature Fusion for Sentence-Level Semantic Similarity Estimation
Venue Joint Conference on Lexical and Computational Semantics
Session
Year 2013
Authors

This paper describes our submission for the *SEM shared task of Semantic Textual Sim- ilarity. We estimate the semantic similarity between two sentences using regression mod- els with features: 1) n-gram hit rates (lexical matches) between sentences, 2) lexical seman- tic 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 indepen- dent models and a model selection strategy achieving a mean correlation of 0.47.