Satya Ranjan Dash

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Post Operative patient dataset is a real world problem obtained from the UCI KDD archive which is used for our classification problem. In this paper different classification techniques such as Bayesian Classification, classification by Decision Tree Induction of data mining and also classification techniques related to fuzzy concepts of soft computing is(More)
In a country like India, the growth rate of the number of academic institutions is at par with the lost student rate. Hence when a lost student is found we need to identify the student on the basis of information such as name of the student, institution name where he studies, class or branch of the student, etc. But the fact is that in most of the cases one(More)
This paper is two folded. In first fold, the authors have illustrated the interplay among fuzzy, rough, and soft set theory and their way of handling vagueness. In second fold, the authors have studied their individual strengths to discover association rules. The performance of these three approaches in discovering comprehensible rules are presented. Usage(More)
In this paper, interactions among fuzzy, rough, and soft set theory has been studied. The authors have examined these theories as a problem solving tool in association rule mining problems of data mining and knowledge discovery in databases. Although fuzzy and rough set have been well studied areas and successfully applied in association rule mining(More)
A shared secret key based symmetric cryptographic algorithm using Diffie Hellman key sharing technique has been proposed in the paper. The shared secret key is used for encryption as well as decryption of the intended plain text. But, we are not transferring the original shared secret key through the channel. We are using Diffie Hellman key sharing(More)
In this paper, a parallel genetic based association rule mining method is proposed to discover interesting rules from a large biological database. Apriori algorithms and its variants for association rule mining rely on two user specified threshold parameters such as minimum support and minimum confidence which is obviously an issue to be resolved. In(More)
The proposed model is mining the interesting association rules based on soft set theory. We have introduced a threshold function in the aforesaid model to eliminate the user defined threshold value for minimum support and confidence to discover interesting rules. In addition, a preprocessing step has been carried out for transforming the quantitative data(More)
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