Periodicity Stream-Mining Using Continuous Database
Periodic stream mining or periodicity detection has a number of applications, such as prediction, forecasting, detection of unusual activities, etc. The data to be analyzed might be noisy (or) perfect data set for which periodicity is to be investigated. There is a need for a comprehensive approach capable of analyzing to handle different types of noise and at the same time is able to detect periodicity for stream-mining using continuous database. The authors required to present an algorithm that can detect periodicity for stream-mining with continuous database.