Abstract
This paper presents a modular approach to context-aware preference query composition based on a novel kind of preference generator. We introduce a constructive model to generate preference terms within the Preference SQL framework. Given several sources for preference related knowledge like explicit user input, information extracted from a preference repository, domain-specific application knowledge, location-based sensor data, or web service feeds for weather data our preference generator can compile a user search request into one rather complex context-aware Preference SQL query. Choosing as use case a commercial e-business platform for outdoor activities, we demonstrate how such queries despite the power and complexity of this approach can be evaluated efficiently on a practical data set.
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Roocks, P., Endres, M., Mandl, S., Kießling, W. (2012). Composition and Efficient Evaluation of Context-Aware Preference Queries. In: Lee, Sg., Peng, Z., Zhou, X., Moon, YS., Unland, R., Yoo, J. (eds) Database Systems for Advanced Applications. DASFAA 2012. Lecture Notes in Computer Science, vol 7239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29035-0_6
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DOI: https://doi.org/10.1007/978-3-642-29035-0_6
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