Search
Search Results
-
IWM-LSTM encoder for abstractive text summarization
Sequence-to-sequence models are fundamental building blocks for generating abstractive text summaries, which can produce precise and coherent...
-
A Comparative Survey of Text Summarization Techniques
Text summarization holds significance in the realm of natural language processing as it expedites the extraction of crucial information from...
-
Machine Learning-Based Automatic Text Summarization Techniques
Automatic text summarization (ATS) technique is needed to create a summary comprising a compact version of significant details of the document. ATS...
-
Contrastive text summarization: a survey
In our data-flooded age, an enormous amount of redundant, but also disparate textual data is collected on a daily basis on a wide variety of topics....
-
A Text Summarization Hybrid Approach Using CNN and the Firefly Algorithm
Automatic text summarization is more significant due to the rapid expansion of textual content on the web and in many archives, such as scientific...
-
A Statistical Language Modeling Framework for Extractive Summarization of Text Documents
The availability of a large collection of text documents on a variety of topics, such as tweets, web pages, news articles, and stories, in different...
-
A knowledge-graph based text summarization scheme for mobile edge computing
As the demand for edge services intensifies, text, being the most common type of data, has seen a significant expansion in data volume and an...
-
Improved hybrid text summarization system using deep contextualized embeddings and statistical features
In this digital world where an enormous volume of textual material is growing on the internet every single day, there is a great need for systems...
-
State-of-the-art approach to extractive text summarization: a comprehensive review
With the rapid growth of social media platforms, digitization of official records, and digital publication of articles, books, magazines, and...
-
Automatic Text Summarization Methods: A Comprehensive Review
Text summarization is the process of condensing a long text into a shorter version by maintaining the key information and its meaning. Automatic text...
-
An entity-guided text summarization framework with relational heterogeneous graph neural network
Two of the most crucial issues for text summarization to generate faithful summaries are to make use of knowledge beyond text and to make use of...
-
A Novel Deep Learning Attention Based Sequence to Sequence Model for Automatic Abstractive Text Summarization
Abstractive text summarization is one of the trending topics in the field of natural language processing (NLP). In this type of text summarization,...
-
Automatic text summarization for government news reports based on multiple features
The purpose of government news summarization is to extract the most important information from official government news reports. It is important for...
-
Large text document summarization based on an enhanced fuzzy logic approach
In today’s digital world, there is an enormous and exponential growth in the amount of knowledge available online. When seeking precise and pertinent...
-
A Hybrid Approach for Automatic Text Summarization by Handling Out-of-Vocabulary Words Using TextR-BLG Pointer Algorithm
AbstractLong documents such as scientific papers and government reports, often discuss substantial issues in long conversation, which are...
-
Text summarization based on semantic graphs: an abstract meaning representation graph-to-text deep learning approach
Nowadays, due to the constantly growing amount of textual information, automatic text summarization constitutes an important research area in natural...
-
Automatic text summarization using deep reinforced model coupling contextualized word representation and attention mechanism
With the rapid and unprecedented growth of textual data in recent years, there is a remarkable need for automatic text summarization models to...
-
EXABSUM: a new text summarization approach for generating extractive and abstractive summaries
Due to the exponential growth of online information, the ability to efficiently extract the most informative content and target specific information...
-
Abstractive text summarization using adversarial learning and deep neural network
A long-term objective of artificial intelligence is to design an abstractive text summarization (ATS) system that can produce condensed, adequate,...
-
An abstractive text summarization technique using transformer model with self-attention mechanism
Creating a summarized version of a text document that still conveys precise meaning is an incredibly complex endeavor in natural language processing...
