dc.contributor.advisor |
Ranathunga S |
|
dc.contributor.author |
Satkunanantham N |
|
dc.date.accessioned |
2021 |
|
dc.date.available |
2021 |
|
dc.date.issued |
2021 |
|
dc.identifier.citation |
Satkunanantham, N. (2021). Monolingual sentence similarity measurement using siamese neural networks for Sinhala and Tamil languages [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/20465 |
|
dc.identifier.uri |
http://dl.lib.uom.lk/handle/123/20465 |
|
dc.description.abstract |
Sentence similarity plays a key role in text-processing related research such as plagiarism checking and paraphrasing. So far, only conventional unsupervised sentence similarity techniques such as string-based, corpus-based, knowledge-based, and hybrid approaches have been used to measure sentence similarity for Tamil and Sinhala languages. In this research, we introduce a Deep Learning methodology to measure sentence similarity for these two languages, which makes use of Siamese Recurrent Neural Networks techniques together with a word-embedding model as the input representation. This approach achieved a 3.07% higher Pearson correlation coefficient for the Tamil dataset of 2500 sentence pairs and a 3.61% higher Pearson correlation coefficient for the Sinhala dataset of 5000 sentence pairs. Both these results outperform that of the conventional unsupervised sentence similarity techniques applied on the same datasets. |
en_US |
dc.language.iso |
en |
en_US |
dc.subject |
SENTENCE-SIMILARITY |
en_US |
dc.subject |
SINHALA, TAMIL |
en_US |
dc.subject |
SIAMESE NEURAL NETWORK |
en_US |
dc.subject |
LSTM |
en_US |
dc.subject |
DEEP-LEARNING |
en_US |
dc.subject |
FASTTEXT |
en_US |
dc.subject |
NATURAL LANGUAGE PROCESSING |
en_US |
dc.subject |
COMPUTER SCIENCE - Dissertation |
en_US |
dc.subject |
COMPUTER SCIENCE & ENGINEERING - Dissertation |
en_US |
dc.subject |
INFORMATION TECHNOLOGY – Dissertation |
en_US |
dc.title |
Monolingual sentence similarity measurement using siamese neural networks for Sinhala and Tamil languages |
en_US |
dc.type |
Thesis-Abstract |
en_US |
dc.identifier.faculty |
Engineering |
en_US |
dc.identifier.degree |
MSc in Computer Science and Engineering |
en_US |
dc.identifier.department |
Department of Computer Science & Engineering |
en_US |
dc.date.accept |
2021 |
|
dc.identifier.accno |
TH4661 |
en_US |