Privacy Preserving on Positive and Negative Pattern Mining in Progressive Database using Noisy Data
Vinti Nanda and Asha Ambhaikar
Department of Computer Science and Engineering, Rungta College of Engineering and Technology, Bhilai-India.
In practice, users are usually more interested in the recent data than the old ones therefore a sequential pattern mining with a progressive database is on demand. The progressive sequential pattern mining deals with a progressive database, which not only adds new data to the original database but also removes obsolete data from the database. Mostly researchers discuss only the positive pattern mining with progressive database; they have not considered the negative pattern mining with a progressive database. Negative pattern mining with a progressive database are very useful in real life problems and are capable of extracting some useful and previously unknown hidden information. In this paper, we discuss positive and negative pattern mining with a progressive database. Further privacy preserving techniques in data mining concept is demanding issues. A procedure to protect the privacy of data by adding noisy items to each transaction is discussed.
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