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EnglishThis 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".
| Titolo: | FBK-HLT: An Effective System for Paraphrase Identification and Semantic Similarity in Twitter |
| Autori: | |
| Data di pubblicazione: | 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". |
| Handle: | http://hdl.handle.net/11582/302181 |
| ISBN: | 978-1-941643-40-2 |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| FBK-HLT- An Effective System for Paraphrase Identification and Semantic Similarity in Twitter.pdf | N/A |  | Open Access Visualizza/Apri |
Utilizza questo identificativo per citare o creare un link a questo documento:
http://hdl.handle.net/11582/302181
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