Abstract
Vectorial representations of words derived from large current events datasets have been shown to perform well on word similarity tasks. This paper shows vectorial representations derived from substantially smaller explanatory text datasets such as English Wikipedia and Simple English Wikipedia preserve enough lexical semantic information to make these kinds of category judgments with equal or better accuracy.
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CITATION STYLE
Jin, L., & Schuler, W. (2015). A comparison of word similarity performance using explanatory and non-explanatory texts. In NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 990–994). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/n15-1101
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