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
2015-01-01
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".File in questo prodotto:
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