Not only will domain experts provide valuable meta data, but also the users from collaborative communities can add such data in the same way. The weight of their opinion and therefore the consequence for the knowledge system depends on the role and the experience of the user. This means that a human domain expert will get a higher weight than a normal user. The weight should be able to dynamically adapt the learning system. The introduced solution makes a combination of knowledge from domain experts and users possible and enables an information flow between both user groups.
Users can use e.g. domain knowledge, base terms or ratings to get relevant information.
On the other side domain experts will sense new trends and locate possibly relevant knowledge pieces by following the users recommendations. It should also be mentioned that users' knowledge how to find sufficient and relevant information regarding a proper topic will become as useful as the knowledge itself. The Knowledge Cluster Human information processing alone will not sufficiently satisfy the present and future requirements on a modern knowledge management system. Automated processes and AI techniques have to be taken into account as well. The automatic process component e.g. may learn from domain knowledge experts and users to provide automatically extracted or generated meta data.