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Conference ProceedingsArtificial Intelligence & Machine Learning

A Systematic Study of Semantic Vector Space Model Parameters

Douwe Kiela·Stephen Charles Clark
2014

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Abstract & Overview

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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Douwe Kiela, Stephen Charles Clark (2014). A Systematic Study of Semantic Vector Space Model Parameters. https://doi.org/10.3115/v1/w14-1503

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Kiela, D., & Clark, S. C. (2014). A Systematic Study of Semantic Vector Space Model Parameters. https://doi.org/10.3115/v1/w14-1503
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