Research On A Data Mining Algorithm Based On Conception Hierarchy Tree And Its Application In CRM

Data mining which means a kind of process that reveals potential useful knowledge from massive, is one important technology in CRM of modem enterprises. Data classification, as an important aspect of research of DM, now has been successfully applied to medical diagnosis, weather prediction, credit approval, customer segmentation, fraud detection and so on.Many different techniques have been proposed for classification, including statistical approaches, neural networks, decision tree algorithm and rough sets. Conception Hierarchy Tree classifiers which is a statistical approach have played an important role in Attribute-Oriented Induction. It can help us discover the characteristics of data, make them more understandable and organized in concept-oriented structure.This dissertation, in the light of the limitations of existed methods, suggest an algorithm based on Conception Hierarchy Tree for data mining, constructing tree from bottom to top through the method of variedly dividing interval and realizing conception hierarchy construction and conception exaltation isochronously.Improved algorithm has showed great effects compared to original algorithm especially to numerical attributes with asymmetry distribution in database. This paper displays the result of two algorithms testing on actual data and offer an example in CRM of a foreign trade enterprise.