Abstract
A typical social networking service contains huge amounts of data, and analyzing this data at the level of the sentence is important. In this paper, we describe our system for a SemEval2015 semantic textual similarity task (task2). We present our approach, which uses edit distance to consider word order, and introduce word appearance in context. We report the results from SemEval2015.
Cite
CITATION STYLE
Miura, N., & Takagi, T. (2015). WSL: Sentence Similarity Using Semantic Distance between Words. In SemEval 2015 - 9th International Workshop on Semantic Evaluation, co-located with the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015 - Proceedings (pp. 128–131). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s15-2023
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