Year: 2018
Type: article
Abstract: This paper proposes a text summarization approach for factual reports using a deep learning model.This approach consists of three phases: feature extraction, feature enhancement, and summary generation, which work together to assimilate core information and generate a coherent, understandable summary.We are exploring various features to improve the set of sentences selected for the summary, and are using a Restricted Boltzmann Machine to enhance and abstract those features to improve resultant accuracy without losing any important information.The sentences are scored based on those enhanced features and an extractive summary is constructed.Experimentation carried out on several articles demonstrates the effectiveness of the proposed approach.
Source: Research in Computing Science
Authors: Sukriti Verma, Vagisha Nidhi
Institution: Delhi Technological University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
Funder: Delhi Technological University
OpenAlex ID: W2747264656