A Review on the Role of Domain Driven Data Mining?

Knowledge Discovery and Data Mining (KDD) refer to the overall process of discovering useful knowledge from data. It involves evaluation and possibly interpretation of the patterns to make decision of what qualifies as knowledge and gives choice of encoding schemes, preprocessing, sampling, and projections of data prior to data mining step. KDD applications in the real world can be as diverse as the real world big databases that exist today thus it lead us to poor knowledge of rich data. Therefore, domain driven data mining (D3M), allow data mining and domain experts to complement each other in regard to in-depth granularity through interactive interfaces. The advantage of D3M over traditional KDD is that, the involvement of domain experts and their knowledge can assist in developing highly effective domain-specific data mining techniques and can reduce the complexity of the knowledge-producing process in the real world business needs. In this study, an attempt is made to identify the role of D3M in the business.