Results 281 to 290 of about 3,357,090 (344)
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YMER Digital, 2022
n the last few years, a huge amount of text data from different sources has been created every day. The enormous data which needs to be processed contains valuable detail which needs to be efficiently summarized so that it serves a purpose. It is very tedious to summarize and classify large amounts of documents when done manually. It becomes cumbersome
Manju D +5 more
openaire +1 more source
n the last few years, a huge amount of text data from different sources has been created every day. The enormous data which needs to be processed contains valuable detail which needs to be efficiently summarized so that it serves a purpose. It is very tedious to summarize and classify large amounts of documents when done manually. It becomes cumbersome
Manju D +5 more
openaire +1 more source
arXiv.org, 2023
Text summarization is a critical Natural Language Processing (NLP) task with applications ranging from information retrieval to content generation. Leveraging Large Language Models (LLMs) has shown remarkable promise in enhancing summarization techniques.
Lochan Basyal, Mihir Sanghvi
semanticscholar +1 more source
Text summarization is a critical Natural Language Processing (NLP) task with applications ranging from information retrieval to content generation. Leveraging Large Language Models (LLMs) has shown remarkable promise in enhancing summarization techniques.
Lochan Basyal, Mihir Sanghvi
semanticscholar +1 more source
T-BERTSum: Topic-Aware Text Summarization Based on BERT
IEEE Transactions on Computational Social Systems, 2022In the era of social networks, the rapid growth of data mining in information retrieval and natural language processing makes automatic text summarization necessary.
Tinghuai Ma +5 more
semanticscholar +1 more source
arXiv.org
Automatic Text Summarization (ATS), utilizing Natural Language Processing (NLP) algorithms, aims to create concise and accurate summaries, thereby significantly reducing the human effort required in processing large volumes of text.
Hanlei Jin +4 more
semanticscholar +1 more source
Automatic Text Summarization (ATS), utilizing Natural Language Processing (NLP) algorithms, aims to create concise and accurate summaries, thereby significantly reducing the human effort required in processing large volumes of text.
Hanlei Jin +4 more
semanticscholar +1 more source
Croatian text summarizer (CROSUM)
27th International Conference on Information Technology Interfaces, 2005., 2005The paper describes automatic summarization of the scientific papers in Croatian language. The goal of the CROSUM is to generate extracts with high percent of extract-worthiness and about the same size as the author's abstract. This preliminary research shows that extracts generated using the lemmatized wordforms dictionary are not quite different from
Lauc, Tomislava +2 more
openaire +2 more sources
A Systematic Survey of Text Summarization: From Statistical Methods to Large Language Models
ACM Computing SurveysText summarization research has undergone several significant transformations with the advent of deep neural networks, pre-trained language models (PLMs), and recent large language models (LLMs).
Haopeng Zhang +2 more
semanticscholar +1 more source