• Narsheedha Beegum. P.A
• Nimal J Valath

Enterprise data mining applications often involve complex data such as multiple large heterogeneous data sources, users preferences, and business impact. In such situations, a single method or one-step mining is often limited in discovering informative knowledge. 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, e.g., integrating frequent pattern mining with classifications to generate frequent pattern-based classifiers. 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, multisource combined mining, and multimethod combined mining. The project implements combined mining approach wth 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.

multi-feature combined mining, multisource combined mining, and multimethod combined mining

"Effective of Combined Mining Techniques with Kinship Search in Complex Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.1, Issue 2, page no.132-138, July-2014, Available :http://www.jetir.org/papers/JETIR1402014.pdf

"Effective of Combined Mining Techniques with Kinship Search in Complex Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.1, Issue 2, page no. pp132-138, July-2014, Available at : http://www.jetir.org/papers/JETIR1402014.pdf