Stream Mining Revisited

摘要

Big data applications have become popular in recent years. Stream mining is one of the major data mining methodologies, which are frequently used in big data applications. Stream mining differenciates itself from the other big data applications for its severe requirement, and is also known for its changing behaviros according to the characteristics of input data. The problem is, however, the parameters, or methodologies for data characterization are not clearly defined yet. There is no study investigating explicit relationships between the characteristics of input data, and the behaviors of stream mining applications. Therefore, the current optimization methodology for stream mining is basically heuristic. This paper provides comprehensive survey on modeling stream mining to seek the strategy for this modeling problem.