Efficient Processing of Top-k Spatial Preference Queries

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Efficient Processing of Top-k Spatial Preference Queries
Top-k spatial preference queries return a ranked set of the k best data objects based on the scores of feature objects in their spatial neighborhood. Despite the wide range of location-based applications that rely on spatial preference queries, existing algorithms incur non-negligible processing cost resulting in high response time. The reason is that computing the score of a data object requires examining its spatial neighborhood to find the feature object with highest score. In this paper, we propose a novel technique to speed up the performance of top-k spatial preference queries. To this end, we propose a mapping of pairs of data and feature objects to a distance-score space, which in turn allows us to identify and materialize the minimal subset of pairs that is sufficient to answer any spatial preference query. Furthermore, we present a novel algorithm that improves query processing performance by avoiding examining the spatial neighborhood of the data objects during query execut...
João B. Rocha-Junior, Akrivi Vlachou, Chris
Added 20 May 2011
Updated 20 May 2011
Type Journal
Year 2010
Authors João B. Rocha-Junior, Akrivi Vlachou, Christos Doulkeridis, Kjetil Nørvåg
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