PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Contextualizing Semantic Representations Using Syntactically Enriched Vector Models
Stefan Thater, Hagen Fuerstenau, and Manfred Pinkal
In: 48th Annual Meeting of the Association for Computational Linguistics, 11-16 July 2010, Uppsala, Sweden.

Abstract

We present a syntactically enriched vector model that supports the computation of contextualized semantic representations in a quasi compositional fashion. It employs a systematic combination of first- and second-order context vectors. We apply our model to two different tasks and show that (i) it substantially outperforms previous work on a paraphrase ranking task, and (ii) achieves promising results on a word-sense similarity task; to our knowledge, it is the first time that an unsupervised method has been applied to this task.

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EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
ID Code:8090
Deposited By:Hagen Fuerstenau,
Deposited On:18 March 2011