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CNGL-CORE: Referential translation machines for measuring semantic similarity

Bicici, Ergun orcid logoORCID: 0000-0002-2293-2031 and van Genabith, Josef orcid logoORCID: 0000-0003-1322-7944 (2013) CNGL-CORE: Referential translation machines for measuring semantic similarity. In: *SEM, 13-14 Jun 2013, Atlanta, Georgia.

Abstract
We invent referential translation machines (RTMs), a computational model for identifying the translation acts between any two data sets with respect to a reference corpus selected in the same domain, which can be used for judging the semantic similarity between text. RTMs make quality and semantic similarity judgments possible by using retrieved relevant training data as interpretants for reaching shared semantics. An MTPP (machine translation performance predictor) model derives features measuring the closeness of the test sentences to the training data, the difficulty of translating them, and the presence of acts of translation involved. We view semantic similarity as paraphrasing between any two given texts. Each view is modeled by an RTM model, giving us a new perspective on the binary relationship between the two. Our prediction model is the $15$th on some tasks and $30$th overall out of $89$ submissions in total according to the official results of the Semantic Textual Similarity (STS 2013) challenge.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:computational semantics; machine translation; machine learning; computational linguistics
Subjects:Computer Science > Computational linguistics
Computer Science > Machine translating
Computer Science > Machine learning
Computer Science > Artificial intelligence
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Next Generation Localisation (CNGL)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Proceedings of *SEM 2013: The Second Joint Conference on Lexical and Computational Semantics. .
Official URL:http://clic2.cimec.unitn.it/starsem2013/
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:18564
Deposited On:10 Jul 2013 09:00 by Mehmet Ergun Bicici . Last Modified 19 Jan 2022 12:44
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