Predicting sense convergence with distributional semantics : an application to the CogALex-IV 2014 shared task

Sitbon, Laurianne & De Vine, Lance (2014) Predicting sense convergence with distributional semantics : an application to the CogALex-IV 2014 shared task. In Zock, Michael, Rapp, Reinhard, & Huang, Chu-Ren (Eds.) Proceedings of the 4th Workshop on Cognitive Aspects of the Lexicon, Dublin, Ireland, pp. 64-67.

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This paper presents our system to address the CogALex-IV 2014 shared task of identifying a single word most semantically related to a group of 5 words (queries). Our system uses an implementation of a neural language model and identifies the answer word by finding the most semantically similar word representation to the sum of the query representations. It is a fully unsupervised system which learns on around 20% of the UkWaC corpus. It correctly identifies 85 exact correct targets out of 2,000 queries, 285 approximate targets in lists of 5 suggestions.

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ID Code: 75447
Item Type: Conference Paper
Refereed: Yes
Keywords: CogALex-IV 2014, Computer linguistics, Neural language model
ISBN: 9781873769331
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 The Authors
Copyright Statement: The papers in this volume are licensed by the authors under a Creative Commons Attribution 4.0 International License.
Deposited On: 24 Aug 2014 23:56
Last Modified: 17 Jul 2017 14:46

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