Modular Implementation of Neural network Structures in Marketing Domain Using Data Mining Technique

The process of implementing neural networks comprises several strategies in the field of data mining. The proper application of
supervised and unsupervised learning concepts play a vital role in the successful implementation of Neural network methods
which are not easily used for data mining tasks. Since they often produce incomprehensible models and require long training
times. In this paper we implement neural network learning algorithms that are able to produce comprehensible models and that do
not require excessive training times. The real time implementation of marketing domain is taken into account for the incorporation
of data mining rule extraction approach which involves extracting symbolic models from trained neural networks. In near future
we will implement the descriptive and predictive approaches of data mining implementation in real time using neural network
conceptual schema.