Intelligent Grid of Computations

Abstract

The Web can be considered a massive information system with interconnected databases and remote applications providing various services. While these services are becoming more and more user oriented, the concept of smart applications on the Web is increasing. Most sites still measure success by hits and page views. Instead, building an intelligent infrastructure to track visitors and their activities could be useful. Web intelligence accurately measures site success and guide future direction. Once built, visitor profile, event, and scenario models will clarify relevant hit measurements. To track users, a three-tiered infrastructure that aggregates, stores, and distributes intelligence across the organization could be build. A middleware platform is required to deal with multiple very-large data sources for multi-aspect analysis intelligence by creating a grid-based of web data mining agents known as Data Mining Grid. As users click banners, view products, and make purchases, and commerce software from the vendors will be filed in a central repository (data Warehouse), typically built on Oracle or Microsoft SQL Server. This Web warehouse will become the definitive repository for clean and consistent organization information. To test hypotheses, non-technical decision-makers will use interactive analysis tools (OLAP and query tools ) from vendors like SAS. OLAP and query tools only answer the questions put to them – they don’t reveal what users should have asked. But Data mining tools uncover hidden trend to find less-obvious knowledge. Data mining tools are available from vendors like DataSage, kapowtech and DBMiner. A multi-level control data mining architecture model included.