A Tensor-Based Approach for Semantic Recommenders in eGovernment

The provision of advanced services for the domain of eGovernment is an active research field. This paper addresses the provision of services in this domain using a semantic-based recommender. Taking a knowledge repository as a starting point, this paper introduces an effective recommendation algorithm to provide the most appropriate services in Public Administration to final users. This algorithm takes the semantic information available in the repository, and transforms it into tensors suitable to be processed in a cost-effective way to provide ordered lists of recommended services. Relevant details on the final implementation of this solution are also discussed.