Scenario-based modeling to capture requirements for immune inspired profile adaptation

Abstract

The human immune system has characteristics such as self-organisation, robustness and adaptivity that may be useful in the development of adaptive systems. One suitable application area for adaptive systems is Information Filtering (IF). Within the context of IF, learning and adapting user profiles is an important research area. In this paper, we proposed an architecture for adaptive IF incorporating ideas from Artificial Immune Systems (AIS). We then extract general features of potential immune inspired profile adaptation based on scenario-based modeling. The richness of scenario usage which we have encountered in this work indicates the importance of comprehensive process guidance.