Abstract
This paper reports the description and performance of our system, FBK-HLT, participating in the SemEval 2015, Task #1 "Paraphrase and Semantic Similarity in Twitter", for both subtasks. We submitted two runs with different classifiers in combining typical features (lexical 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".
Cite
CITATION STYLE
Vo, N. P. A., Magnolini, S., & Popescu, O. (2015). FBK-HLT: An Effective System for Paraphrase Identification and Semantic Similarity in Twitter. In SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings (pp. 29–33). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s15-2005
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