Abstract
This paper describes FCICU team systems that participated in SemEval-2017 Semantic Textual Similarity task (Task1) for monolingual and cross-lingual sentence pairs. A sense-based language independent textual similarity approach is presented, in which a proposed alignment similarity method coupled with new usage of a semantic network (BabelNet) is used. Additionally, a previously proposed integration between sense-based and sur-face-based semantic textual similarity approach is applied together with our proposed approach. For all the tracks in Task1, Run1 is a string kernel with alignments metric and Run2 is a sense-based alignment similarity method. The first run is ranked 10th, and the second is ranked 12th in the primary track, with correlation 0.619 and 0.617 respectively- Anthology ID:
- S17-2015
- Volume:
- Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Venue:
- SemEval
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 125–129
- Language:
- URL:
- https://aclanthology.org/S17-2015
- DOI:
- 10.18653/v1/S17-2015
- Cite (ACL):
- Basma Hassan, Samir AbdelRahman, Reem Bahgat, and Ibrahim Farag. 2017. FCICU at SemEval-2017 Task 1: Sense-Based Language Independent Semantic Textual Similarity Approach. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 125–129, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- FCICU at SemEval-2017 Task 1: Sense-Based Language Independent Semantic Textual Similarity Approach (Hassan et al., SemEval 2017)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S17-2015.pdf