Knowledge Discovery in Data-Mining
Completion requirements
Knowledge discovery in databases (KDD) is discovering useful knowledge from data collection. The data mining process aims to extract information from a data set and transform it into an understandable structure for further use. Data mining is just one step of the knowledge discovery process (the core step). Some following steps are pattern evaluation (this step interprets mined patterns and relationships), akin to your analytic process, and knowledge consolidation, similar to reporting your findings, although they ought to be more robust than simply consolidating knowledge to respond responsibly to your requirements. Like analysis, KDD is an iterative process. If the pattern evaluated after the data mining step is not useful, the process can begin again from the previous steps.
11. Conclusion
In this paper, the characteristics of Data Mining of knowledge is were studied. We have concentrated here on different angles of KDD mean, KDD process, Academic Research Models, Steps of Knowledge Discovery in Database, Knowledge Discover Process, Industrial Model, Knowledge discovery process.