Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/2154
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Chathurika, W. M. T | - |
dc.contributor.author | De Silva, K. C | - |
dc.contributor.author | Raddella, A. M | - |
dc.contributor.author | Ekanayake, E. M. R. S | - |
dc.contributor.author | Nugaliyadde, A | - |
dc.contributor.author | Mallawarachchi, Y | - |
dc.date.accessioned | 2022-05-03T03:49:31Z | - |
dc.date.available | 2022-05-03T03:49:31Z | - |
dc.date.issued | 2018-09-11 | - |
dc.identifier.citation | arXiv:1809.04557 [cs.CL] (or arXiv:1809.04557v1 [cs.CL] | en_US |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/2154 | - |
dc.description.abstract | A methodology is presented to solve Arithmetic problems in Sinhala Language using a Neural Network. The system comprises of (a) keyword identification, (b) question identification, (c) mathematical operation identification and is combined using a neural network. Naïve Bayes Classification is used in order to identify keywords and Conditional Random Field to identify the question and the operation which should be performed on the identified keywords to achieve the expected result. “One vs. all Classification” is done using a neural network for sentences. All functions are combined through the neural network which builds an equation to solve the problem. The paper compares each methodology in ARIS and Mahoshadha to the method presented in the paper. Mahoshadha2 learns to solve arithmetic problems with the accuracy of 76%. | en_US |
dc.language.iso | en | en_US |
dc.publisher | arxiv logo > cs > arXiv:1809.04557 | en_US |
dc.relation.ispartofseries | arXiv preprint arXiv:1809.04557; | - |
dc.subject | Natural Language Processing (NLP) | en_US |
dc.subject | Artificial Neural Network | en_US |
dc.subject | CRF++ tool | en_US |
dc.subject | Naïve Bayes Algorithm | en_US |
dc.title | Solving Sinhala Language Arithmetic Problems using Neural Networks | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.48550/arXiv.1809.04557 | en_US |
Appears in Collections: | Research Papers - Open Access Research Research Papers - SLIIT Staff Publications Research Publications -Dept of Information Technology |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
1809.04557.pdf | 658.86 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.