User Profile Generation Based on a Memory Retrieval Theory

Several statistical approaches for user profiling have been proposed in order to recognize users’ information needs during their interaction with information sources. Human memory processes in terms of learning and retrieval are with no doubt some of the fundamental elements that take part during this interaction, but actually only a few models for user profiling have been devised considering explicitly these processes. For this reason, a new approach for user modeling is proposed and evaluated. The grounds in the well-studied Search of Associative Memory (SAM) model provides a clear definition of the structure to store information and the processes of learning and retrieval. These assets are missing in other works based for example on simplified versions of semantic memory models and co-occurrence data.