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Paper Details

Paper Title
Secure Multi-Modal Summarization Using LexRank Algorithm
Abstract
Text summarization aims to condense a source text into a shorter version. Automatic data summarization is part of data mining. The rapid growth in data transmission over the internet makes it necessary to create multi-modal summarization (MMS) from asynchronous data (text, audio, and video). In this work, an MMS method combining the techniques of natural language processing (NLP), speech processing, computer vision and advanced encryption standard (AES) encryption is used to explore the rich information contained in multi-modal data, to improve the quality and security as well the key idea is to bridge and lessen the semantic gaps between multi-modal data. Video is basically composed of audio and visual (image). For audio, speech transcriptions are used. For visual information, the joint representations of image and text is studied using an artificial neural network. Finally, all the multi-modal aspects are considered to generate a textual summary by maximizing the salience, readability, non- redundancy. The summary so generated by text, audio or video is encrypted using AES encryption method (to make it secure) and stored on server, from where the user can retrieve it whenever required by providing the decryption key.
Keyword
AES, Encryption, Decryption, Summarization, Multimedia, Multi-modal, Natural language processing, Computer vision.
Others Details
Paper Id : 19180
Author Name : AKSHAY SHEGAONKAR
Co-Author Name(s) : HARSHALANUPAMA ANAND PANDEAISHWARYA KAMTIKARMANGESH MANAKE
Volume/Issue No : Volume 07 Issue 06
Page No : 13-17
DOI Number : DOI:10.21090/IJAERD.19180
License : This work is licensed under a Creative Commons Attribution 4.0 International License.
website : http://www.ijaerd.com/index.php
Impact Factor : 5.71, SJIF-2017
ISSN Details : eISSN: 2348-4470, pISSN:2348-6406
Evden Eve Nakliyat