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FCICU at SemEval-2017 Task 1: Sense-Based Language Independent Semantic Textual Similarity Approach
- Source :
- SemEval@ACL
- Publication Year :
- 2017
- Publisher :
- Association for Computational Linguistics, 2017.
-
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
- Subjects :
- Computer science
business.industry
02 engineering and technology
computer.software_genre
Semantic network
SemEval
Semantic similarity
Ranking
Similarity (network science)
String kernel
020204 information systems
Semantic computing
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
Artificial intelligence
business
computer
Semantic compression
Natural language processing
Sentence
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
- Accession number :
- edsair.doi...........3183c64e46680406c226e8d18be81be6
- Full Text :
- https://doi.org/10.18653/v1/s17-2015