Search
9 articles for “Automatic text summarization”
-
TextSum: An Automatic Text Summarization Tool using Bayesian Classification
Abstract: Automatic text summarization is the process of summarizing text from one or more documents in order to help the reader to determine if [s]he has to read the document(s) in full. Although automatic summarization is around for many years, there is a renewed interest in this area from the government, industry, and academia. The reason is the availability of large quantities of information due to world wide web and the …
Published in Recent Trends in Programming languages · Vol. 1, Issue 1, 2014 · pp. 1–3 Read article
-
Automatic Text Summarization – A Review
Abstract: ABSTRACT We present Encoder/Decoder a unique methodology for summarization of text documents. The summarization of text is to be done in two forms one is abstractive and the other one is extractive. Summarization of text is a main job of natural language processing. With the help of new idea we make a unique amalgam model of abstractive-extractive to combine BERT(Bidirectional Encoder Representations from Transformers). Firstly we transform the summaries which …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 3, 2020 · pp. 22–27 Read article
-
Semantic Summarizer
Abstract: Abstract: This work presents the survey of the existing approaches used for automatic text summarization. Automatic text summarization technique belongs to the natural language processing area, and is applied on the source document to produce its compact version that preserves its aggregate meaning and key concepts. On a broader scale, approaches for text summarization task are classified into two categories: (1) abstractive and (1) extractive. In abstractive summarization, main contents …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 6, Issue 3, 2019 · pp. 1–8 Read article
-
A Strategical Review on Text Summarization
Abstract: Text summarization is the important component of the document analysis. Reading the complete set of documents if the work is tedious, so that the summary presents the brief idea about the whole document. In this paper we review the concept of the automatic text summarization and the concept involved in the automatic text summarization.Cite this ArticlePankaj Kumar, Komal Sharma*. A Strategical Review on Text Summarization. Research & Reviews: A Journal …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 6, Issue 3, 2018 · pp. 8–12 Read article
-
Audio Summarization of Podcasts
Abstract: Podcasts have emerged as a significant medium for disseminating information, sharing stories, and providing entertainment. As their popularity continues to soar, the sheer volume of available content poses a challenge for listeners seeking to efficiently consume information. In this context, creating and deploying an audio summarizer for podcasts becomes highly significant. This research paper delves into the motivation for creating such a tool, emphasizing the increasing need for concise and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
-
Exploring Technologies for Extractive Text Summarization: A Review of Transformer and Reinforcement Learning Models
Abstract: In recent years, the size of information on the Internet has increased exponentially. Therefore, a solution is needed to transform large amounts of raw data into useful information the human brain can understand. Automatic Text Summarization (ATS) is a part of Natural Language Processing (NLP) that aims to take long texts and shorten them, keeping the most important information in a clear and easy-to-understand way. This research report explores methods …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article
-
Text Summarizer using NLP (Natural Language Processing)
Abstract: Enormous amounts of information are available online on the World Wide Web. To access information from databases, search engines like Google and Yahoo were created. Because the amount of electronic information is growing every day, the real outcomes have not been reached. As a result, automated summarization is in high demand. Automatic summary takes several papers as input and outputs a condensed version, saving both information and time. The study …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 3, 2021 · pp. 1–6 Read article
-
Exam Eval: An Automated Model for Correcting Exam Papers Using OCR and Text Summarization
Abstract: In the realm of education, grading and correcting exam papers can be a time-consuming and often daunting task for teachers. To streamline this process and provide more efficient feedback to students, this project aims to develop a model that leverages advanced techniques in natural language processing (NLP) and computer vision. The primary objective is to correct exam papers by summarizing the handwritten answers provided by students, incorporating Optical Character Recognition …
Published in Journal of Web Engineering & Technology · Vol. 10, Issue 3, 2023 · pp. 23–28 Read article
-
Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article