The Spatial Nearest Neighbor Skyline Queries
Nasrin Mazaheri Soudani, Ahmad Baraani-Dastgerdi

TL;DR
This paper introduces spatial nearest neighbor skyline queries, a new user preference query type in spatial databases that evaluates locations based on distances to nearest neighbors, avoiding complex attribute weighting.
Contribution
It proposes a novel query type and an efficient N2S2 algorithm for computing it, improving performance over traditional skyline query methods.
Findings
N2S2 algorithm outperforms branch and bound in efficiency
New query type simplifies user preference specification
Applicable in service recommendation and investment planning
Abstract
User preference queries are very important in spatial databases. With the help of these queries, one can found best location among points saved in database. In many situation users evaluate quality of a location with its distance from its nearest neighbor among a special set of points. There has been less attention about evaluating a location with its distance to nearest neighbors in spatial user preference queries. This problem has application in many domains such as service recommendation systems and investment planning. Related works in this field are based on top-k queries. The problem with top-k queries is that user must set weights for attributes and a function for aggregating them. This is hard for him in most cases. In this paper a new type of user preference queries called spatial nearest neighbor skyline queries will be introduced in which user has some sets of points as query…
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Taxonomy
TopicsData Management and Algorithms · Geographic Information Systems Studies · Constraint Satisfaction and Optimization
