CORPURES: Benchmark corpus for urdu extractive summaries and experiments using supervised learning

Autor: Muhammad Humayoun, Naheed Akhtar

Publikováno v: Intelligent Systems with Applications, Vol 16, Iss , Pp 200129- (2022)

Text summarization is the process of shortening the text so that it conveys the key points. Several text summarization methods and benchmark corpora are available for languages like English. A significant hurdle in developing and evaluating existing

Externí odkaz: https://doaj.org/article/680d3f5e20d3403593efd31098f82dca

A Survey on Multi-document Summarization and Domain-Oriented Approaches

Autor: Afsharizadeh, Mahsa, Ebrahimpour-Komleh, Hossein, Bagheri, Ayoub, Chrupala, Grzegorz, Leerstoel Oberski, Methodology and statistics for the behavioural and social sciences

Publikováno v: Journal of Information Systems and Telecommunication, 10(37), 68-79. Iranian Academic Center for Education, Culture and Research
Journal of Information Systems and Telecommunication, 10(37), 68. Iranian Academic Center for Education, Culture and Research

Before the advent of the World Wide Web, lack of information was a problem. But with the advent of the web today, we are faced with an explosive amount of information in every area of search. This extra information is troublesome and prevents a quick

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::468b65c582edfce8bd214db735664ca3
https://research.tilburguniversity.edu/en/publications/db47beed-bab4-46ef-a5c9-5cf1614b33aa

An Automatic Persian Text Summarization System Based on Linguistic Features and Regression

Autor: Mahmood Soltani, Jalal Nasiri, Ehsan Asgarian

Publikováno v: Iranian Journal of Information Processing & Management, Vol 33, Iss 4, Pp 1809-1828 (2018)

Considering the vast amount of existing written information and the shortage of time, optimal summarization of books, articles, news reports, etc. on the Web is a major concern of researchers. In this paper, we propose a new approach for Persian sing

Externí odkaz: https://doaj.org/article/4f4e6ec7aaf6465eba9947d9c6370f9f

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A Framework for Extractive Text Summarization Based on Deep Learning Modified Neural Network Classifier

Autor: Sivaparthipan Cb, Rubén González Crespo, Ching-Hsien Hsu, Seifedine Kadry, Oscar Sanjuan, BalaAnand Muthu, Priyan Malarvizhi Kumar

Publikováno v: Re-Unir. Archivo Institucional de la Universidad Internacional de La Rioja
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There is an exponential growth of text data over the internet, and it is expected to gain significant growth and attention in the coming years. Extracting meaningful insights from text data is crucially important as it offers value-added solutions to

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a0b32a0bbb71cc69a09c15154518ed3
https://doi.org/10.1145/3392048