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Hybrid Auto Text Summarization Using Deep Neural Network and Fuzzy Logic System - 2017

Hybrid Auto Text Summarization Using Deep Neural Network And Fuzzy Logic System

Research Paper on Hybrid Auto Text Summarization Using Deep Neural Network And Fuzzy Logic System

Research Area:  Machine Learning

Abstract:

Amount of text for a particular topic is increasing at an exponential rate each day, causing availability of bulk text data, some of which will be relevant to our search while some data may be irrelevant. In such case we need to summarize the text document, so as to understand the key elements of the document. A Hybrid Automatic Summarizer using soft computing techniques namely, Fuzzy logic system and deep neural system is proposed. The summary is based on extractive summarization technique. Restricted boltzman Machine (RBM) is used in the deep neural network and fuzzy rule base on the sentences for feature extraction using a sentence matrix. Evaluation of hybridized systems gave better summary as compared to the individual systems.

Keywords:  
Text Summarization
Deep Neural Network
Fuzzy Logic System
Restricted boltzman Machine
Machine Learning
Deep Learning

Author(s) Name:   Heena A. Chopade; Meera Narvekar

Journal name:  

Conferrence name:  International Conference on Inventive Computing and Informatics (ICICI)

Publisher name:  IEEE

DOI:   10.1109/ICICI.2017.8365192

Volume Information: