R. R. Rajalaxmi

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A new stream of research privacy preserving data mining emerged due to the recent advances in data mining, Internet and security technologies. Data sharing among organizations considered to be useful which offer mutual benefit for business growth. Preserving the privacy of shared data for clustering was considered as the most challenging problem. To(More)
In Internet applications, due to the growth of big data with more features, intrusion detection has become a difficult process in terms of computational complexity, storage efficiency and getting optimized solutions of classification through existing sequential computing environment. Using a parallel computing model and a nature inspired feature selection(More)
Data mining plays a vital role in today's information world wherein it has been widely applied in various business organizations. The current trend in business collaboration demands the need to share data or mined results to gain mutual benefit. However it has also raised a potential threat of revealing sensitive information when releasing data. Data(More)
— Machine learning has been an effective support system in medical diagnosis which involve large amount of data. Analyzing such data consumes more time in terms of execution and resources. All data features do not support for the end results. Hence it is very important to identify the features that contribute more in identifying the diseases. Those with(More)
Background: Social Network Mining is the most emerging area in the Data Mining. Now a days predicting spammers in online social networking sites had become a difficult challenge due to large number of features. In the recent existing works only the dependency of each feature from the face book towards classification is analyzed and there was no work to(More)
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