International Journal of Advance Computational Engineering and Networking (IJACEN)
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Feb. 2023
Submitted Papers : 80
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  Journal Paper

Paper Title :
An Overview of Hashing Techniques Using Neural Network

Author :Mrinal Jyoti Deka

Article Citation :Mrinal Jyoti Deka , (2017 ) " An Overview of Hashing Techniques Using Neural Network " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 17-21, Volume-5, Issue-2

Abstract : For efficient and strong positive output in any industry, it is necessary to analyze the data involved in it; data analysis becomes a part of success in any projects. Therefore, research on big data is increasing day by day to find and design efficiently any updates related to any field. As in much application like large scale search, comparing and matching pattern, it has become difficult to have a straightforward solution due to limitations of computational complexity and consumption of large space requirement for memory. As a solution for this many approaches like Approximate Nearest Neighbor search based on hashing techniques and other randomized hashing methods have gained popularity, but the interpretation of them in many real-world applications has been proven to be insufficient. In the meanwhile many advanced methods to analyze the big data by in cooperating data-driven learning methods in the development of advanced hash functions have emerged. However, till date, no systematic review has been undertaken to analyse and summarize hashing technique using neural network. This paper mainly covers the trend of hashing techniques and its advanced methods in applications, activities described in the many sectors. The findings indicate that the popularity of this technique, its pros and cons. Overall Paper provides a comprehensive overview of articles published in academic journals. The review provides stakeholders with valuable information on the hashing approaches and about advanced hash functions. Keywords- Big Data, Hashing techniques, Machine Learning and ANN.

Type : Research paper

Published : Volume-5, Issue-2


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