Enhancing traditional local search recommendations with context-awareness

Authors:
Claudio Biancalana;Andrea Flamini;Fabio Gasparetti;Alessandro Micarelli;Samuele Millevolte;Giuseppe Sansonetti
Affiliations:
Artificial Intelligence Laboratory, Roma Tre University, Rome, Italy;Artificial Intelligence Laboratory, Roma Tre University, Rome, Italy;Artificial Intelligence Laboratory, Roma Tre University, Rome, Italy;Artificial Intelligence Laboratory, Roma Tre University, Rome, Italy;Artificial Intelligence Laboratory, Roma Tre University, Rome, Italy;Artificial Intelligence Laboratory, Roma Tre University, Rome, Italy
Venue:
UMAP'11 Proceedings of the 19th international conference on User modeling, adaption, and personalization
Year:
2011

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Abstract

Traditional desktop search paradigm often does not fit mobile contexts. Common mobile devices provide impoverished mechanisms for text entry and small screens are able to offer only a limited set of options, therefore the users are not usually able to specify their needs. On a different note, mobile technologies have become part of the everyday life as shown by the estimate of one billion of mobile broadband subscriptions in 2011. This paper describes an approach to make context-aware mobile interaction available in scenarios where users might be looking for categories of points of interest (POIs), such as cultural events and restaurants, through remote location-based services. Empirical evaluations shows how rich representations of user contexts has the chance to increase the relevance of the retrieved POIs.