A system of agent-based software patterns for user modeling based on usage mining

In adaptive hypermedia systems, a user can select explicitly an adaptation effect or he/she can leave the system execute some of these functions. An important component of an adaptive system is the ability to model the users of the system according to their goals and preferences. Web usage mining aims at discover interesting patterns of use by analyzing Web usage data. This information can be used to capture implicitly user models and used them for the adaptation of systems. User modeling and system adaptability can be approached through the agent paradigm. This article summarizes a system of architectural and detailed design patterns describing known agent-based solutions to recurrent problems of user modeling based on usage mining along with the description of a general purpose problem-solving architectural pattern used by some of the first ones. Patterns are derived from recurrent designs of specific agent-based applications. The proposed patterns are being developed in the context of a Multi-Agent Domain Engineering research project, which approaches software complexity and productivity through the construction of techniques and tools promoting software reuse in Multi-Agent Domain Engineering.