International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Survey Paper | Computer Science & Engineering | India | Volume 4 Issue 9, September 2015 | Popularity: 6.7 / 10


     

Survey on Discrimination Analysis and Sentimental Analysis in Text Mining by using NLP Method

Bhagyashri Sawana, P. K. Bharne


Abstract: Discrimination Analysis is the prejudicial treatment which involves denying opportunities to members of one group in favor of other groups. It is unfair to discriminate people because of their gender, religion, nationality, age and so on, especially when those attributes are used for making decisions about them like giving them a job, loan, insurance, etc. the training data without harming their decision-making utility is therefore highly desirable which forms the primary goal of anti-discrimination techniques in data mining. The evolution of web technology, there is a huge amount of data present in the web for the internet users. These users not only use the available resources in the web, but also give their feedback, thus generating additional useful information. Due to overwhelming amount of users opinions, views, feedback and suggestions available through the web resources, its very much essential to explore, analyze and organize their views for better decision making. In this paper we are survey Opinion Mining or Sentiment Analysis is a Natural Language Processing and Information Extraction task that identifies the users views or opinions explained in the form of positive, negative or neutral.


Keywords: Discrimination, Sentimental SVM, NLP


Edition: Volume 4 Issue 9, September 2015


Pages: 1029 - 1033



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Bhagyashri Sawana, P. K. Bharne, "Survey on Discrimination Analysis and Sentimental Analysis in Text Mining by using NLP Method", International Journal of Science and Research (IJSR), Volume 4 Issue 9, September 2015, pp. 1029-1033, https://www.ijsr.net/getabstract.php?paperid=SUB158067, DOI: https://www.doi.org/10.21275/SUB158067



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