BL.Research at SemEval-2022 Task 8: Using various Semantic Information to evaluate document-level Semantic Textual Similarity
Sebastien Dufour, Mohamed Mehdi Kandi, Karim Boutamine, Camille Gosse, Mokhtar Boumedyen Billami, Christophe Bortolaso, Youssef Miloudi
Abstract
This paper presents our system for document-level semantic textual similarity (STS) evaluation at SemEval-2022 Task 8: “Multilingual News Article Similarity”. The semantic information used is obtained by using different semantic models ranging from the extraction of key terms and named entities to the document classification and obtaining similarity from automatic summarization of documents. All these semantic information’s are then used as features to feed a supervised system in order to evaluate the degree of similarity of a pair of documents. We obtained a Pearson correlation score of 0.706 compared to the best score of 0.818 from teams that participated in this task.- Anthology ID:
- 2022.semeval-1.173
- Volume:
- Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Editors:
- Guy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1221–1228
- Language:
- URL:
- https://preview.aclanthology.org/icon-24-ingestion/2022.semeval-1.173/
- DOI:
- 10.18653/v1/2022.semeval-1.173
- Cite (ACL):
- Sebastien Dufour, Mohamed Mehdi Kandi, Karim Boutamine, Camille Gosse, Mokhtar Boumedyen Billami, Christophe Bortolaso, and Youssef Miloudi. 2022. BL.Research at SemEval-2022 Task 8: Using various Semantic Information to evaluate document-level Semantic Textual Similarity. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1221–1228, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- BL.Research at SemEval-2022 Task 8: Using various Semantic Information to evaluate document-level Semantic Textual Similarity (Dufour et al., SemEval 2022)
- PDF:
- https://preview.aclanthology.org/icon-24-ingestion/2022.semeval-1.173.pdf
- Code
- jln-brtn/bl.research-at-semeval-2022-task-8