An Overview of Hashing Techniques Using Neural Network
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.