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TKLBLIIR: Detecting Twitter Paraphrases with TweetingJay
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
doi:10.18653/v1/s15-2012
dblp:conf/semeval/KaranGSBVM15
fatcat:jgmhtqci65h6tlyg2wws6flchm