This paper describes the HHU system that participated in Task 2 of SemEval 2017, Multilingual and Cross-lingual Semantic Word Similarity. We introduce our unsupervised embedding learning technique and describe how it was employed and configured to address the problems of monolingual and multilingual word similarity measurement. This paper reports from empirical evaluations on the benchmark provided by the task's organizers.
CITATION STYLE
Qasemizadeh, B., & Kallmeyer, L. (2017). HHU at SemEval-2017 Task 2: Fast Hash-Based Embeddings for Semantic Word Similarity Assessment. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (pp. 250–255). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s17-2039
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