Results 61 to 70 of about 3,357,090 (344)

Extractive social media text summarization based on MFMMR-BertSum

Array, 2023
The advancement of computer technology has led to an overwhelming amount of textual information, hindering the efficiency of knowledge intake. To address this issue, various text summarization techniques have been developed, including statistics, graph ...
Junqing Fan, Xiaorong Tian, Chengyao Lv, Simin Zhang, Yuewei Wang, Junfeng Zhang   +5 more
doaj   +1 more source

Text Summarization Challenge: An Evaluation Program for Text Summarization [PDF]

, 2020
In Japan, the Text Summarization Challenge (TSC), the first text summarization evaluation of its kind, was conducted in 2000–2001 as a part of the NTCIR (NII-NACSIS Test Collection for IR Systems) Workshop. The purpose of the workshop was to facilitate collecting and sharing text data for summarization by researchers in the field and to clarify the ...
Hidetsugu Nanba, Tsutomu Hirao, Takahiro Fukushima, Manabu Okumura   +3 more
openaire   +1 more source

BART-IT: An Efficient Sequence-to-Sequence Model for Italian Text Summarization

Future Internet, 2022
The emergence of attention-based architectures has led to significant improvements in the performance of neural sequence-to-sequence models for text summarization. Although these models have proved to be effective in summarizing English-written documents,
Moreno La Quatra, Luca Cagliero
semanticscholar   +1 more source

Automatic Text Summarization of COVID-19 Research Articles Using Recurrent Neural Networks and Coreference Resolution

Frontiers in Biomedical Technologies, 2020
Purpose: Pandemic COVID-19 has created an emergency for the medical community. Researchers require extensive study of scientific literature in order to discover drugs and vaccines.
Mahsa Afsharizadeh, Hossein Ebrahimpour-Komleh, Ayoub Bagheri   +2 more
doaj   +1 more source

Automatic Text Summarization

International Journal for Research in Applied Science and Engineering Technology, 2023
Abstract: Text Summarization is a Natural Language Processing (NLP) method that extracts and collects data from the source and summarizes it. Text summarization has become a requirement for many applications since manually summarizing vast amounts of information is difficult, especially with the expanding magnitude of data.
Sakshi Jawale, Pranit Londhe, Prajwali Kadam, Sarika Jadhav, Rushikesh Kolekar   +4 more
openaire   +1 more source

Text Summarization and Translation of Summarized Outcome in French [PDF]

E3S Web of Conferences, 2023
Automatic text summarization is increasingly required with the exponential growth of unstructured text through increasing internet and social media usage across the globe. The various approaches are outcomes of extraction-based and abstraction-based.
Vetriselvi T., Mathur Mihir
doaj   +1 more source

Multidocument Arabic Text Summarization Based on Clustering and Word2Vec to Reduce Redundancy

Information, 2020
Arabic is one of the most semantically and syntactically complex languages in the world. A key challenging issue in text mining is text summarization, so we propose an unsupervised score-based method which combines the vector space model, continuous bag ...
Samer Abdulateef, Naseer Ahmed Khan, Bolin Chen, Xuequn Shang   +3 more
doaj   +1 more source

Improved Text Summarization of News Articles Using GA-HC and PSO-HC

Applied Sciences, 2021
Automatic Text Summarization (ATS) is gaining attention because a large volume of data is being generated at an exponential rate. Due to easy internet availability globally, a large amount of data is being generated from social networking websites, news ...
Muhammad Mohsin, Shazad Latif, Muhammad Haneef, Usman Tariq, Muhammad Attique Khan, Sefedine Kadry, Hwan-Seung Yong, Jung-In Choi   +7 more
doaj   +1 more source

Extractive Text Summarization

International Journal of Advanced Research in Science, Communication and Technology, 2022
In this fast paced technological era, where huge quantity of information is generating on the internet day by day. Since the dotcom bubble burst back in 2000, technology has radically transformed our societies. So, it is necessary to provide the better mechanism to extract the useful information fast and most effectively.
null Vivek S. Bhore, null Pratik Bondare, null Rutik D. Gawande, null Vrushabh V. Guntiwar, null Priti V. Kale   +4 more
openaire   +1 more source

Enhancing E-Recruitment Recommendations Through Text Summarization Techniques

Information
This research aims to enhance e-recruitment systems using text summarization techniques and pretrained large language models (LLMs). A job recommender system is built with integrated text summarization. The text summarization techniques that are selected
Reham Hesham El-Deeb, Walid Abdelmoez, Nashwa El-Bendary   +2 more
doaj   +1 more source