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2008 Volume 23
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RESEARCH ARTICLE   Open Access    

Situational reasoning for task-oriented mobile service recommendation

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  • Abstract: We study the case of integrating situational reasoning into a mobile service recommendation system. Since mobile Internet services are rapidly proliferating, finding and using appropriate services require profound service descriptions. As a consequence, for average mobile users it is nowadays virtually impossible to find the most appropriate service among the many offered. To overcome these difficulties, task navigation systems have been proposed to guide users towards best-fitting services. Our goal is to improve the user experience of such task navigation systems making them context-aware (i.e. to optimize service navigation by taking the user's situation into account). We propose the integration of a situational reasoning engine that applies classification-based inference to qualitative context elements, gathered from multiple sources and represented using ontologies. The extended task navigator enables the delivery of situation-aware recommendations in a proactive way. Initial experiments with the extended system indicate a considerable improvement of the navigator's usability.
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  • Cite this article

    MARKO LUTHER, YUSUKE FUKAZAWA, MATTHIAS WAGNER, SHOJI KURAKAKE. 2008. Situational reasoning for task-oriented mobile service recommendation. The Knowledge Engineering Review. 23: doi: 10.1017/S0269888907001300
    MARKO LUTHER, YUSUKE FUKAZAWA, MATTHIAS WAGNER, SHOJI KURAKAKE. 2008. Situational reasoning for task-oriented mobile service recommendation. The Knowledge Engineering Review. 23: doi: 10.1017/S0269888907001300

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RESEARCH ARTICLE   Open Access    

Situational reasoning for task-oriented mobile service recommendation

The Knowledge Engineering Review  23 Article number: 10.1017/S0269888907001300  (2008)  |  Cite this article

Abstract: Abstract: We study the case of integrating situational reasoning into a mobile service recommendation system. Since mobile Internet services are rapidly proliferating, finding and using appropriate services require profound service descriptions. As a consequence, for average mobile users it is nowadays virtually impossible to find the most appropriate service among the many offered. To overcome these difficulties, task navigation systems have been proposed to guide users towards best-fitting services. Our goal is to improve the user experience of such task navigation systems making them context-aware (i.e. to optimize service navigation by taking the user's situation into account). We propose the integration of a situational reasoning engine that applies classification-based inference to qualitative context elements, gathered from multiple sources and represented using ontologies. The extended task navigator enables the delivery of situation-aware recommendations in a proactive way. Initial experiments with the extended system indicate a considerable improvement of the navigator's usability.

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    Cite this article
    MARKO LUTHER, YUSUKE FUKAZAWA, MATTHIAS WAGNER, SHOJI KURAKAKE. 2008. Situational reasoning for task-oriented mobile service recommendation. The Knowledge Engineering Review. 23: doi: 10.1017/S0269888907001300
    MARKO LUTHER, YUSUKE FUKAZAWA, MATTHIAS WAGNER, SHOJI KURAKAKE. 2008. Situational reasoning for task-oriented mobile service recommendation. The Knowledge Engineering Review. 23: doi: 10.1017/S0269888907001300
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