Context-aware Reputation Framework (CaRF)

Abstract

Reputation a key factor in day-to-day decision making is making inroads to computer systems as well. While computer systems are becoming more and more interconnected and 'social networking' become more and more promising digital reputation gains high attention. Context is an important aspect of reputation which is widely and conveniently ignored in reputation systems. But without context, reputation will be single faceted and of less use. This dissertation proposes a reputation framework which incorporates context into the reputation and supports upcoming Semantic Web concepts. It also proposes the usage of Subjective Logic as the mechanism to calculate reputation as it resembles the o human nature closely. The discussion of this work is on a minimal implementation of such a framework which would serve the basis for future enhancements. Ill