Single-Document Myanmar Text Summarization using Latent Semantic Analysis (LSA)

Abstract

Due to an exponential growth in the generation of textual data, 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, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSA is a retrieval method that uses a mathematical technique called singular value decomposition (SVD) to identify patterns in the relationships between the terms and concepts contained in an unstructured collection of text. There is no LSA based sentence extraction in Myanmar language. This is the first LSA based Text Summarizer in Myanmar. We summarize Myanmar news from Myanmar official websites such as 7day daily, new-eleven, ThithtooLwin, etc.