Type

Conference Proceedings

Authors

Andy Way
Ergun Bicici

Subjects

Linguistics

Topics
artificial intelligence translation machine translating semantic similarity machine learning computational model computational linguistics training data

RTM-DCU: referential translation machines for semantic similarity (2014)

Abstract We use referential translation machines (RTMs) for predicting the semantic similarity of text. RTMs are a computational model for identifying the translation acts between any two data sets with respect to interpretants selected in the same domain, which are effective when making monolingual and bilingual similarity judgments. RTMs judge the quality or the semantic similarity of text by using retrieved relevant training data as interpretants for reaching shared semantics. We derive features measuring the closeness of the test sentences to the training data via interpretants, the difficulty of translating them, and the presence of the acts of translation, which may ubiquitously be observed in communication. RTMs provide a language independent approach to all similarity tasks and achieve top performance when predicting monolingual cross-level semantic similarity (Task 3) and good results in semantic relatedness and entailment (Task 1) and multilingual semantic textual similarity (STS) (Task 10). RTMs remove the need to access any task or domain specific information or resource.
Collections Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Computational linguistics
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres
Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> Subject = Computer Science: Artificial intelligence
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Centre for Next Generation Localisation (CNGL)
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools
Ireland -> Dublin City University -> Subject = Computer Science: Machine translating
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing
Ireland -> Dublin City University -> Subject = Computer Science: Machine learning

Full list of authors on original publication

Andy Way, Ergun Bicici

Experts in our system

1
Andy Way
Dublin City University
Total Publications: 229
 
2
Ergun Bicici
Dublin City University
Total Publications: 12