A Systematic Study of Semantic Vector Space Model Parameters
نویسندگان
چکیده
We present a systematic study of parameters used in the construction of semantic vector space models. Evaluation is carried out on a variety of similarity tasks, including a compositionality dataset, using several source corpora. In addition to recommendations for optimal parameters, we present some novel findings, including a similarity metric that outperforms the alternatives on all tasks considered.
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تاریخ انتشار 2014