AEC Personalization framework for regulation retrieval

The paper gives an overview of the personalization framework in the frames of the CONNIE project. The focus on the improvement of the Information Retrieval (IR) of regulations leads to the research question: How can personalization for AEC stakeholders improve regulation IR in built environment? The corner stones of the presented approach are: user profiling, personalization, localization and collaborative filtering. We adopted iterative Survey-Test (ST) rapid prototyping which was found very powerful and led to effective implementation of the system. We present important aspects of the user profiling that is a crucial mechanism for the design, implementation and constant improvement of any information retrieval system. The framework is based on the personalization taxonomy that addresses what, why, and how can be personalized. We define data profile categories for AEC users, which can be static and/or dynamic. In the presented prototype we also suggest a generic conceptual solution enabling open implementation of the personalization.