Abstract
Business Monitoring is a complex task and it has been noted that most of the reporting and analysis time is being spent on collecting data from the various systems. Over the past decade, a lot of research has been reported on Decision Support Systems (DSS) used in many fields. To improve the decision-making ability of an enterprise in construction management, information technology is being applied in each step of construction management. The problem is to organize and analyze the data in construction management to obtain quick analysis and decision support results. Various Data mining techniques have been used for clustering of data by using case examples. In this research we have applied Learning Vector Quantization (LVQ) to classify projects in one of the given categories and conducted a comparative analysis by using standard algorithm. A number of case examples have been used to verify the results and to obtain a comparison between various methodologies.