Adaptive Recommendation and Open-Ended Semiosis

A recommendation system for an extended process of information retrieval in distributed information systems is proposed. This system is both a model of dynamic cognitive categorization processes and powerful real application useful for knowledge management. It utilizes an extension of fuzzy sets named evidence sets as the mathematical mechanisms to implement the categorization processes. It is a development of some aspects of Pask’s Conversation Theory. It is also an instance of the notion of linguistic-based selected self-organization here described, and as such it instantiates an open-ended semiosis between distributed information systems and the communities of users they interact with. This means that the knowledge stored in distributed information resources adapts to the evolving semantic expectations of their users as these select the information they desire in conversation with the information resources. This way, this recommendation system establishes a mechanism for user-driven knowledge self-organization.