Intelligent information systems: new techniques and applications.

The immense popularity of the Internet and recent technological innovations in storage technology have caused a true tsunami of data. The need to build intelligent information systems, targeted at learning patterns from data and subsequently deploying them in key business processes, is now stronger than ever before (Baesens et al. 2006; Baesens 2003). In this research proposal, I plan to start with outlining the theoretical research objectives related to how to build intelligent information systems by developing new predictive algorithms for rule extraction using both Support Vector Machines (SVM) and Ant Colony Optimization (ACO) techniques, with extensions for dealing with domain knowledge, small data sets and networked observations. I will hereby extensively rely on my research expertise gained in the past, and combine this with recent, new ideas that will undoubtedly lead to interesting, new groundbreaking scientific findings. I will validate the newly developed algorithms in several practical, real-life problem settings. It will be noted that the suggested research is multi-disciplinary in nature, having a core management informatics focus, but with clear links to finance, marketing and statistics. In what follows, I will further elaborate on both types of research objectives and the corresponding research methodologies.

Keywords:Informatica, Data Mining, Financial Engineering

Disciplines:Applied mathematics in specific fields