An experimental evaluation of ontology-based user profiles

Abstract

In recent years, a number of research works have been carried out to improve the information retrieval process by exploiting external knowledge, e.g., by employing ontologies. Even though ontologies seem to be a promising technique to improve the retrieval process, hardly any study has been performed to evaluate the use of ontologies over a longer time period to model user interests. In this work we introduce an ontology based video recommender system that exploits implicit relevance feedback to capture users' evolving information needs. The system exploits a generic ontology to organise users' interests. We evaluate the recommendations by performing a user-centred multiple time-series study where participants were asked to include the system into their daily news gathering routine. The results of this study suggest that the system can be successfully employed to improve personal information seeking tasks in news domain.

Continuous Evaluation of Large-Scale Information Access Systems: A Case for Living Labs

“…Breaking news events add another source for variation. This is in particular challenging for recommendation techniques that rely on exploiting users' prior interaction with news items (e.g., (Hopfgartner and Jose, 2014)). • The online component of NewsREEL causes additional challenges that need to be considered in order to guarantee a fair and unbiased evaluation.…”