Ranking by Quality in Spatial Data Using Top-k Preference Theory
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Abstract
This spatial preference query ranks objects based on the qualities of features in their spatial neighbourhood. For example, using a real estate agency database of flats for lease, a customer may want to rank the flats with respect to the appropriateness of their location, defined after aggregating the qualities of other features (e.g., restaurants, cafes, hospital, market, etc.) within their spatial neighbourhood. Such a neighbourhood concept can be specified by the user via different functions. It can be an explicit circular region within a given distance from the flat. Another intuitive definition is to consider the whole spatial domain and assign higher weights to the features based on their proximity to the flat. We formally define spatial preference queries and propose appropriate indexing techniques and search algorithms for them. Extensively evaluation of our methods on both real and synthetic data reveals that an optimized branch-and-bound solution is efficient and robust with respect to different parameters
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Keywords: Databases, Spatial Data, Spatial databases, querying, analysis of data, ranking data, query processing.
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