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  1. University of Information Technology
  2. Faculty of Computer Science

Extractive Summarization for Myanmar Language

https://meral.edu.mm/records/6759
https://meral.edu.mm/records/6759
bc01b59e-1583-4bf7-93fc-f37a5006d41e
441d16da-0092-4a49-8661-65b4eeb6ffec
Publication type
Conference paper
Upload type
Publication
Title
Title Extractive Summarization for Myanmar Language
Language en
Publication date 2018-11-01
Authors
Soe Soe Lwin
Khin Thandar Nwet
Description
Due to increasing availability of online information, tools and mechanisms for automatic summarization of documents is needed. Text summarization is currently a major research topic in Natural Language Processing. There are various approaches to generate text summary. Among them, we proposed Myanmar text summarization using latent semantic analysis (LSA). Latent semantic analysis (LSA) is a technique in natural language processing,and can analyze relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. It is an unsupervised approach which does not need any traning or external knowledge. There is no LSA based sentence extraction in Myanmar language. This is the first LSA based Text Summarizer in Myanmar. This paper present generic, extractve and single-document Myanmar text summarization using latent semantic analysis. This paper compare two sentence selection methods (Steinberger and Jezek's approach and Ozay approach) of latent semantic analysis to extract important sentences. We summarize Myanmar news from Myanmar official websites such as 7day daily, iyarwaddy, etc.,.
Keywords
LSA, text summarization
Identifier 10.1109/iSAI-NLP.2018.8692976
Conference papers
iSAI-NLP
November, 2018
2018 International Joint Symposium on Artificial Intelligence and Natural Language Processing
Pattaya, Thailand
https://ieeexplore.ieee.org/document/8692976
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