Provided by: International Journal of Computer Science and Mobile Computing (IJCSMC)
Topic: Data Management
Date Added: Apr 2015
Classification and patterns extraction from customer data is very important factors for business support and decision making. Identification of newly emerging trends is needed in business process. Sales patterns from inventory data indicate market trends and can be used in forecasting which has great potential for decision making, strategic planning and market competition. The system consists of two phases. In the first phase, the authors divide the stock data in three different clusters on the basis of product categories and sold quantities i.e. Dead-Stock (DS), Slow-Moving (SM) and Fast-Moving (FM) using K-means algorithm.