Analysis and evaluation of distributed knowledge management by agent-based simulation

Abstract

Knowledge and Information Management can often be applied successfully only, if it allows for a certain degree of heterogeneity and organizational distribution. Distributed Knowledge and Information Management enable loosely coupled collaboration in heterogeneous domains by intelligent automatic mediation. One major obstacle in the development of such mediation methods is systematic evaluation. This work presents an approach to evaluate intelligent mediation techniques for Distributed Knowledge and Information Management using agent-based modeling and simulation. On the one hand, the proposed model can be used to gain insight into the problems that heterogeneity poses on such mediation methods. On the other hand, it can be used to predict the performance of a system, before actually introducing it in an organization.

The framework is instantiated for two different tasks. Firstly, it is applied to the problem of collaborative filtering, a relatively well studied approach to mediate ratings among heterogeneous users and user groups. This area serves as a test-bed for the simulation framework and is used to analyze some prototypical problems faced in many Distributed Information and Knowledge Management systems. In a second instantiation, the model is applied to the problem of matching concepts in different ontologies.