Results 101 to 110 of about 168,037 (222)

Statistical Approaches to Automatic Text Summarization [PDF]

Bulletin of the American Society for Information Science and Technology, 2004
La production automatisee de resume repose sur deux approches de base, l'extraction de texte fondee sur l'analyse statistique, et l'extraction de faits, beaucoup plus complexe. L'extraction de texte statistique consiste a ponderer les mots en fonction de leur frequence.
openaire   +1 more source

Generalized minimum dominating set and application in automatic text summarization

, 2016
For a graph formed by vertices and weighted edges, a generalized minimum dominating set (MDS) is a vertex set of smallest cardinality such that the summed weight of edges from each outside vertex to vertices in this set is equal to or larger than certain
Xu, Yi-Zhi, Zhou, Hai-Jun
core   +1 more source

Keyword Detection in Text Summarization [PDF]

, 2015
Summarization is the process of reducing a text document in order to create a summary that retains the most important points of the original document.
Thomas, Justine Raju
core  

A Text Abstraction Summary Model Based on BERT Word Embedding and Reinforcement Learning

Applied Sciences, 2019
As a core task of natural language processing and information retrieval, automatic text summarization is widely applied in many fields. There are two existing methods for text summarization task at present: abstractive and extractive.
Qicai Wang, Peiyu Liu, Zhenfang Zhu, Hongxia Yin, Qiuyue Zhang, Lindong Zhang   +5 more
doaj   +1 more source

Retracted: Automatic Text Summarization for Public Health WeChat Official Accounts Platform Base on Improved TextRank. [PDF]

J Environ Public Health, 2023
Environmental And Public Health JO.
europepmc   +1 more source

MTL-DAS: Automatic Text Summarization for Domain Adaptation. [PDF]

Comput Intell Neurosci, 2022
Zhong J, Wang Z.
europepmc   +1 more source

Automatic Text Summarization Approaches to Speed up Topic Model Learning Process

, 2016
The number of documents available into Internet moves each day up. For this reason, processing this amount of information effectively and expressibly becomes a major concern for companies and scientists.
Dufour, Richard, Linarès, Georges, Morchid, Mohamed, Ramírez-Rodríguez, Javier, Torres-Moreno, Juan-Manuel   +4 more
core  

Small language models applied in text summarization task of health-related news to improve public health audit: an experimental case study

Frontiers in Artificial Intelligence
ContextFraud and corruption are among the main crimes affecting public institutions, with the healthcare sector being particularly vulnerable due to its structural complexity, the coexistence of public and private providers, the large number of actors ...
Alysson Guimarães, Methanias Colaço Junior, Methanias Colaço Junior, Samuel Santana De Almeida, Gabriely Garcia Ferreira de Araújo, Raphael Silva Fontes, Helder Prado, Helder Prado, Luca Pareja Credidio Freire Alves, Natan Matos, Ricardo Alexsandro de Medeiros Valentim, João Paulo Queiroz dos Santos   +11 more
doaj   +1 more source

Integrating Document Structure into a Multi-Document Summarizer

, 2009
International audienceIn this paper, we present a novel approach for automatic summarization. CBSEAS, the system implementing this approach, integrates a method to detect redundancy at its very core, in order to produce more expressive summaries than ...
Bossard, Aurélien, Poibeau, Thierry
core  

Automatic Text Summarization Methods

International Journal for Research in Applied Science and Engineering Technology
Withtheexponentialincreaseindigitalinformation, the challenge of information overload has become critical. Automatic Text Summarization (ATS) offers a solution by distilling keyinformationfromlargetextsintoconcisesummaries.ThispaperexploresATSmethodologies,focusingonclassificationsbased on input type, purpose, and output type.
openaire   +1 more source