SMARTMUSEUM: A Mobile Recommender System for the Web of Data

Tuukka Ruotsalo, Krister Haav, Antony Stoyanov, Silvain Roche, Elena Fani, Romina Deliai, Eetu Mäkelä, Tomi Kauppinen, Eero Hyvönen

Abstract


Semantic and context knowledge have been envisioned as an appropriate solution for addressing the content heterogeneity and information overload in mobile Web information access, but few have explored their full potential inmobile scenarios, where information objects refer to their physical counterparts, and retrieval is context-aware and personalized for users. We present SMARTMUSEUM, a mobile ubiquitous recommender system for the Web of Data, and its application to information needs of tourists in context-aware, on-site access to cultural heritage. The SMARTMUSEUM system utilizes Semantic Web languages as the form of data representation. Ontologies are used to bridge the semantic gap between heterogeneous content descriptions, sensor inputs, and user profiles. The system makes use of an information retrieval framework where in context data and search result clustering are used in recommendation of suitable content for mobileusers. Results from laboratory experiments demonstrate that ontology-based reasoning, query expansion, search result clustering, and context knowledge lead to significant improvement in recommendation performance. The results from field trials show that the usability of the system meets users’ expectations in real-world use. The results indicate that semantic content representation and retrieval can significantly improve the performance of mobile recommender systems in knowledge-rich domains.

Full Text: PDF
Type of Paper: System Paper
Keywords: Web of Data, Semantic Web, Information Retrieval, Recommender Systems, Mobile Systems, User Profiling Structured Data, Ubiquitous Computing, Cultural Heritage
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