Multi-Document Text Summarization Using Deep Learning Algorithm with Fuzzy Logic

6 Pages Posted: 23 Apr 2018

See all articles by S.Sudha Lakshmi

S.Sudha Lakshmi

Sri Padmavati Mahila Visvavidyalayam (SPMVV)

M. Usha Rani

Sri Padmavati Mahila Visvavidyalayam (SPMVV)

Date Written: February 7, 2018

Abstract

Multi-document text summarization focuses on extracting the key information from the collection of related documents and presents it as a brief summary.In this paper, we are presenting multi document text summarization using Deep learning algorithm with fuzzy logic which is an important research area in NLP, data mining(DM) and Machine Learning(ML). To improve the accuracy here , we are using Restricted Boltzman machine to generate a shortend version of original document without losing its valuable information. The current method consists of two steps: 1.Training phase 2. Testing phase. The prominent role of the training phase is to extract effective summary generation. Afterwards the testing phase is implemented to validate the efficiency and accuracy of the proposed method.

Keywords: Deep Learning, Fuzzy Logic, Multi-document Summary, RBM

Suggested Citation

Lakshmi, S.Sudha and Rani, M. Usha, Multi-Document Text Summarization Using Deep Learning Algorithm with Fuzzy Logic (February 7, 2018). 2018 IADS International Conference on Computing, Communications & Data Engineering (CCODE), Available at SSRN: https://ssrn.com/abstract=3165331 or http://dx.doi.org/10.2139/ssrn.3165331

S.Sudha Lakshmi (Contact Author)

Sri Padmavati Mahila Visvavidyalayam (SPMVV) ( email )

Padmavathi Nagar, Near West Railway Station,
Andhra Pradesh
Tirupati, Andhra Pradesh 517502
India

M. Usha Rani

Sri Padmavati Mahila Visvavidyalayam (SPMVV) ( email )

Padmavathi Nagar, Near West Railway Station,
Andhra Pradesh
Tirupati, Andhra Pradesh 517502
India

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