A Survey on Novel approach to prevent Direct and Indirect Discrimination in Dataset retrievals
Author(s):
Ria Patel, Richa Agrawal
Keywords:
Data mining, Discrimination, Pre-processing, In-processing, Post-processing
Abstract
Data mining is an important technology for extracting useful patterns from large amount of data.There are some negative approaches in data mining like potential privacy incursion and potential discrimination. Discrimination consists of unfairly treating people on the basis of their belonging to a specific group. Automated data collection and data mining techniques such as classification rule mining have paved the way to making automated decisions, like loan granting/denial, insurance premium computation, etc. Discrimination occurs when people are given unfair treatment on the basis of their sensitive features like gender, race, religion etc. there are two type of discrimination. One is direct discrimination and other is indirect discrimination. Indirect discrimination is when there’s a practice, policy or rule which applies to everyone in the same way, but it has a worse effect on some people than others. If you’ve been treated unfairly by someone simply because of who you are, this could be direct discrimination. The analysis of literature survey would give the information about what has been done previously in the same area, what is the current trend and what are the other related areas. We have prepare algorithm with the help of classification rules for discriminatory free dataset and we get accurate result without damaging original data.
Article Details
Unique Paper ID: 144216

Publication Volume & Issue: Volume 3, Issue 8

Page(s): 150 - 152
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