This paper reports the description and perfor- mance of our system, FBK-HLT, participating in the SemEval 2015, Task #1 "Paraphrase and Semantic Similarity in Twitter", for both sub- tasks. We submitted two runs with different classifiers in combining typical features (lexi- cal similarity, string similarity, word n-grams, etc) with machine translation metrics and edit distance features. We outperform the baseline system and achieve a very competitive result to the best system on the first subtask. Eventually, we are ranked 4th out of 18 teams participating in subtask "Paraphrase Identification".

FBK-HLT: An Effective System for Paraphrase Identification and Semantic Similarity in Twitter

Ngoc Phuoc An, Vo;Magnolini, Simone;Popescu, Octavian
2015

Abstract

This paper reports the description and perfor- mance of our system, FBK-HLT, participating in the SemEval 2015, Task #1 "Paraphrase and Semantic Similarity in Twitter", for both sub- tasks. We submitted two runs with different classifiers in combining typical features (lexi- cal similarity, string similarity, word n-grams, etc) with machine translation metrics and edit distance features. We outperform the baseline system and achieve a very competitive result to the best system on the first subtask. Eventually, we are ranked 4th out of 18 teams participating in subtask "Paraphrase Identification".
978-1-941643-40-2
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/302181
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