Organizing Multiple Data Sources for Developing Intelligent e-Business Portals

Abstract

Enterprise applications usually involve huge, complex, and persistent data to work on, together with business rules and processes. In order to represent, integrate, and use the information coming from the huge, distributed, multiple sources, we present a conceptual model with dynamic multi-level workflows corresponding to a mining-grid centric multi-layer grid architecture, for multi-aspect analysis in building an e-business portal on the Wisdom Web. We show that this integrated model will help to dynamically organize status-based business processes that govern enterprise application integration. We also present two case studies to demonstrate the effectiveness of the proposed model in the real world. The first case study is about how to organize and mine multiple data sources for behavior-based online customer segmentation, which is the first crucial step of personalization and one-to-one marketing. The second case study is about how to evaluate and monitor data quality, which in return can optimize the knowledge discovery process for intelligent decision making. The proposed methodology attempts to orchestrate various mining agents on the mining-grid for integrating data and knowledge in a unified portal developed by a service-oriented architecture.