Effective of Combined Mining Techniques with Kinship Search in Complex Data

Enterprise data mining applications usually involve complex data such as multiple large heterogeneous data sources, users preferences, and business impact. A single method or one-step mining is limited in discovering informative knowledge in such situations. Mining complex data causes more space complexity and time complexity. It is crucial to develop effective approaches for mining patterns combining necessary information. The recent years have seen increasing efforts on mining more informative patterns. The project proposes combined mining as a general approach, rather than presenting a specific algorithm. Combined mining is a framework for mining informative patterns by combining components from either multiple data sets or multiple features or by multiple methods on demand. Proposed general frameworks, paradigms, and basic processes for multi-feature combined mining, multi-source combined mining, and multi-method combined mining using existing algorithms. The project implements combined mining approach with kinship search technique to generate the effective patterns in medical field. By observing informative patterns acquired from the above techniques efficient actionable decision making is possible.