ASOBEK at SemEval-2016 Task 1: Sentence representation with character N-gram embeddings for semantic textual similarity

Eyecioglu, Asli and Keller, Bill (2016) ASOBEK at SemEval-2016 Task 1: Sentence representation with character N-gram embeddings for semantic textual similarity. In: SemEval-2016: The 10th International Workshop on Semantic Evaluation: proceedings of the Workshop: June 16-17, 2016, San Diego, California, USA. Association for Computational Linguistics (ACL), Stroudsburg, PA, pp. 1320-1324. ISBN 9781941643952

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Abstract

A growing body of research has recently been conducted on semantic textual similarity using a variety of neural network models. While re- cent research focuses on word-based represen- tation for phrases, sentences and even paragraphs, this study considers an alternative approach based on character n-grams. We generate embeddings for character n-grams using a continuous-bag-of-n-grams neural network model. Three different sentence rep- resentations based on n-gram embeddings are considered. Results are reported for experi- ments with bigram, trigram and 4-gram em- beddings on the STS Core dataset for SemEval-2016 Task 1.

Item Type: Book Section
Schools and Departments: School of Engineering and Informatics > Informatics
Subjects: P Language and Literature > P Philology. Linguistics > P0098 Computational linguistics. Natural language processing
Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
Depositing User: Bill Keller
Date Deposited: 23 Jun 2016 11:10
Last Modified: 23 Jun 2016 11:15
URI: http://sro.sussex.ac.uk/id/eprint/61686

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