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17 results for “Text Summarization”

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Review ArticleOpen accessPhrase in the titleA Review on Automatic Text Summarization ApproachesYogan Jaya Kumar, Ong Sing Goh, Halizah Basiron et al.It has been more than 50 years since the initial investigation on automatic text summarization was started. Various techniques have been successfully used to extract the important contents from text document to represent document summary. In this study, we review some of the studies that have been conducted in this still-developing research area. It covers the basics of text summarization, … …Journal of Computer Science, Vol. 12, Issue 4 · 30 Apr 2016 · 10,361 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleImplementation and Evaluation of Evolutionary Connectionist Approaches to Automated Text SummarizationUday Kulkarni, Rajesh Shardanand PrasadProblem statement: Text summarization takes care of choosing the most significant portions of text and generates coherent summaries that express the main intent of the given document. This study aims to compare the performances of the three text summarization systems developed by the authors with some of the existing Summarization systems available. These three approaches to text summarization are based … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 8,489 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFuzzy Swarm Based Text SummarizationMohammed Salem Binwahlan, Naomie Salim, Ladda SuanmaliProblem statement: The aim of automatic text summarization systems is to select the most relevant information from an abundance of text sources. A daily rapid growth of data on the internet makes the achieve events of such aim a big challenge. Approach: In this study, we incorporated fuzzy logic with swarm intelligence; so that risks, uncertainty, ambiguity and imprecise values … …Journal of Computer Science, Vol. 5, Issue 5 · 30 May 2009 · 7,412 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleText Summarization Using Morphological Filtering of Intuitionistic Fuzzy HypergraphDhanya Prabhasadanam Mohanan, Sreekumar Ananda Rao, Jathavedan Madambi, Ramkumar Padinjarepizharath BalakrishnaText Summarization has been an area of interest for many years. It refers to creating a concise text of a document without any lose of information. Researchers in the area of natural language processing have developed many abstractive and extractive methods for creating summary. Abstractive summaries modifies the sentences and creates a modified concise form, while extractive summaries pick relevant … …Journal of Computer Science, Vol. 14, Issue 6 · 25 Jun 2018 · 7,871 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAN APPROACH FOR TEXT SUMMARIZATION USING DEEP LEARNING ALGORITHMG. PadmaPriya, K. DuraiswamyNow days many research is going on for text summarization. Because of increasing information in the internet, these kind of research are gaining more and more attention among the researchers. Extractive text summarization generates a brief summary by extracting proper set of sentences from a document or multiple documents by deep learning. The whole concept is to reduce or minimize … …Journal of Computer Science, Vol. 10, Issue 1 · 7 Nov 2013 · 7,803 accessesView PDFCite
Research ArticleOpen accessIn the keywordsDetecting Disinformation: Enriching the COVAX Reality Dataset with BERT for Stance DetectionSaad Ahmed, Asma Qaiser, Sidrah Abdullah, Muhammad Shoaib SiddiquiSocial media news pages and online news portals have significantly grown in popularity among the users across the globe for accessing the latest and important news. Unlike traditional newspapers, online news portals and social media provide the news round the clock and can be accessed from any location free of cost. However, the internet sources, especially the social media, have … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 1,836 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Deep Learning Approach for Telugu Domain Identification with Multichannel LSTM-CNNBuddha Hari Kumar, Chitra Perumal, Inakoti Ramesh Raja et al.The vast growth of textual data has ushered into the limelight, a plethora of applications in information retrieval and natural language processing (NLP). Proper extraction of information from text is heavily dependent on recognizing the thematic content, which becomes crucial in the tasks of document summarization, information extraction, question answering, machine translation, and sentiment analysis. The great complexity of this … …Journal of Computer Science, Vol. 21, Issue 9 · 26 Nov 2025 · 2,395 accessesView PDFCite
Research ArticleOpen accessIn the keywordsModelling Knowledge Summarization by Evolving Fuzzy GrammarNurfadhlina Mohd Sharef, Alfian Abdul Halin, Norwati MustaphaSummarized text is a simplified and condensed version of the original text containing highlighted information to help the audience get the gist in a short period of time. Typically, text summarization produces abstract or a paragraph-like outputs by omitting details and irrelevant information. However, the text summary can also be produced in a visualized form, such as a chart, graph … …American Journal of Applied Sciences, Vol. 10, Issue 6 · 10 Jun 2013 · 6,659 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAutomatic Multi Document Summarization ApproachesYogan Jaya Kumar, Naomie SalimProblem statement: Text summarization can be of different nature ranging from indicative summary that identifies the topics of the document to informative summary which is meant to represent the concise description of the original document, providing an idea of what the whole content of document is all about. Approach: Single document summary seems to capture both the information well but … …Journal of Computer Science, Vol. 8, Issue 1 · 1 Nov 2011 · 8,712 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAbstractive Summarization of Long Educational Transcripts in the Era of GenAIDeepa Fernandes, Rupali Sunil WaghThe surge in online video data presents the imperative requirement of summarizing it for information compression, efficient understanding, and to support decision-making. Recent research studies have predominantly utilized structured input data for summarization. This paper explores the current state-of-the-art models in summarizing unstructured, conversational, and long transcript data. We further apply a transfer learning approach using a fine-tuned BART model, … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 403 accessesView PDFCite