Automatic Amharic Text Summarization using NLP Parser

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2017 by IJETT Journal
Volume-53 Number-1
Year of Publication : 2017
Authors : Getahun Tadesse Mekuria, Aniket S. Jagtap
DOI :  10.14445/22315381/IJETT-V53P210


Getahun Tadesse Mekuria, Aniket S. Jagtap "Automatic Amharic Text Summarization using NLP Parser", International Journal of Engineering Trends and Technology (IJETT), V53(1),52-58 November 2017. ISSN:2231-5381. published by seventh sense research group

The proposed system investigates the problem of building the domain based single and multiple document Amharic text summarization. Multi-document summarization is the main task in natural language processing and summarizing a huge text document into a short and precise format from multiple documents. Multi-document summarization targets to condense the most important information from a set of documents to produce a short summary. Multi-document summarization is also an integral tool for document understanding and well interpreting in the existing system of text summarization. But single text document summarization has been done from a single text document only. Text summarization can be done based on its input, purpose, and output. In the existing system, most research has been done on extractive single document summarization, but now we propose the new system that solves the existing problem by developing the combinations of extractive and abstractive summarization approach on a single as well as multiple document input from the user. To solve such existing problem by using Java programming language for their flexibility and it has a powerful library Java universal network graphic for text summary. PageRank algorithm plays a great role in finding out their sentence score and its weights of a sentence in the document. The proposed model summarizes only text document but in the future, develop text summarization model for all types of document including graph, image, picture, video and other form in addition to the text document.

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JUNG, Amharic Text summary, Abstractive, Extractive summarization, Domainbased summarization, MDS, AATS, JAMA.