TY - GEN
T1 - GWU NLP at SemEval-2016 shared task 1
T2 - 10th International Workshop on Semantic Evaluation, SemEval 2016
AU - Aldarmaki, Hanan
AU - Diab, Mona
N1 - Publisher Copyright:
© 2016 Association for Computational Linguistics.
PY - 2016
Y1 - 2016
N2 - We present a matrix factorization model for learning cross-lingual representations for sentences. Using sentence-aligned corpora, the proposed model learns distributed representations by factoring the given data into language-dependent factors and one shared factor. As a result, input sentences from both languages can be mapped into fixed-length vectors and then compared directly using the cosine similarity measure, which achieves 0.8 Pearson correlation on Spanish-English semantic textual similarity.
AB - We present a matrix factorization model for learning cross-lingual representations for sentences. Using sentence-aligned corpora, the proposed model learns distributed representations by factoring the given data into language-dependent factors and one shared factor. As a result, input sentences from both languages can be mapped into fixed-length vectors and then compared directly using the cosine similarity measure, which achieves 0.8 Pearson correlation on Spanish-English semantic textual similarity.
UR - http://www.scopus.com/inward/record.url?scp=85035804814&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85035804814&partnerID=8YFLogxK
U2 - 10.18653/v1/s16-1101
DO - 10.18653/v1/s16-1101
M3 - Conference contribution
AN - SCOPUS:85035804814
T3 - SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings
SP - 663
EP - 667
BT - SemEval 2016 - 10th International Workshop on Semantic Evaluation, Proceedings
PB - Association for Computational Linguistics (ACL)
Y2 - 16 June 2016 through 17 June 2016
ER -