TKLBLIIR: Detecting Twitter Paraphrases with TweetingJay

Mladen Karan, Goran Glavaš, Jan Šnajder, Bojana Dalbelo Bašić, Ivan Vulić, Marie-Francine Moens
2015 Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015)  
When tweeting on a topic, Twitter users often post messages that convey the same or similar meaning. We describe TweetingJay, a system for detecting paraphrases and semantic similarity of tweets, with which we participated in Task 1 of SemEval 2015. TweetingJay uses a supervised model that combines semantic overlap and word alignment features, previously shown to be effective for detecting semantic textual similarity. TweetingJay reaches 65.9% F1-score and ranked fourth among the 18
more » ... g systems. We additionally provide an analysis of the dataset and point to some peculiarities of the evaluation setup.
doi:10.18653/v1/s15-2012 dblp:conf/semeval/KaranGSBVM15 fatcat:jgmhtqci65h6tlyg2wws6flchm