Knowledge sharing is one of the modern knowledge management initiatives, where a more user-centered system has replaced the traditional management of knowledge as asset. This article aims to collect user satisfaction to prove whether user profiling and recommendation is significant in knowledge sharing facilitation framework. A four-factor evaluation metric to measure the overall performance of the agent based system is used. The evaluation metric consists of three types of analysis, which are overlap analysis, weighted responds analysis and responds analysis. The four-factor metric covers the efficiency of user profile built by the agent, the relevance of recommendation, the staff directory and the document repository. The main discussion is on the setting of the experiment and the results of KSFaci performance in the proposed experiment setting. It is concluded that user profiling and recommendation plays a role in knowledge sharing system framework.

User Satisfaction, Agent-based Knowledge Sharing System