Analytical Data Mining for Stream Data Analysis

The main idea behind this research relies on analytical data mining functions to handle data streams. Given the characteristics of the data stream, the new methods and techniques for stream data analysis must conduct advanced analysis and data mining over fast and large data streams to capture the trends, patterns and exceptions. Besides, much of such data resides at rather low level of abstraction, whereas most analysts are interested in dynamic changes at relatively high levels of abstractions. Furthermore, recently studies are heading to combine ideas of cube-based algorithms with data mining functions to reveal exceptional and trend patterns over data streams. Thus, this work intends to provide new methods for effective and efficient analytical data mining over data streams.