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Volume & Issue no: Volume 4, Issue 2, February 2015

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Title:
Direct and Indirect Discrimination Prevention in Data Mining By Using Natural Language Method
Author Name:
Ms Shraddha S Kediya, Prof S.V.Dabhade
Abstract:
ABSTRACT In data mining, discrimination is a very important issue when considering the legal and ethical aspects of privacy preservation. It is more clear that most of the people do not have a wish to discriminated based on their race, nationality, religion, age and so on. This problem mainly arises when these kind of attributes are used for decision making purpose such as giving them a job and loan. Automatic data collection has become the most wanted method in the banking sector to make automatic decisions like loan granting/denial. Part-of-Speech (POS) tagging is the process of assigning a part-of-speech like noun, verb, adjective, adverb, or other lexical class marker to each word in a sentence. This paper presents a POS Tagger for English language text using Rule based approach, which will assign part of speech to the words in a sentence given as an input. n this paper we are going to use Natural Language Processing Approach for direct and indirect discrimination prevention. It consists of POS tagging and chunking methods. POS tagging is useful for identifying verbs, nouns, adjectives in a given line. On the basis of that we can identify the action words which may cause direct or indirect discrimination. Keyword:- Direct discrimination, Indirect discrimination ,NLP,POS etc.
Cite this article:
Ms Shraddha S Kediya, Prof S.V.Dabhade , " Direct and Indirect Discrimination Prevention in Data Mining By Using Natural Language Method" , International Journal of Application or Innovation in Engineering & Management (IJAIEM) , Volume 4, Issue 2, February 2015 , pp. 073-079 , ISSN 2319 - 4847.
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