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Breaking the Top-κ Restriction of the kNN Hidden Databases
Li H.; Gong Z.
Source PublicationProceedings - 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016
AbstractWith the increasing development of Location-based services (LBS), the spatial data become accessible on the web. Often, such services provide a public interface which allows users to find k nearest points to an arbitrary query point. These services may be abstractly modeled as a hidden database behind a kNN query interface, we refer it as a kNN hidden database. The kNN interface is the only way we can access such hidden databases and can be quite restrictive. A key restriction enforced by such a kNN interface is the Top-κ output constraint - i.e., given an arbitrary query, the system only returns the k nearest points to the query point (where k is typically a small number such as 10 or 50), hence, such restriction prevents many third-party services from being developed over the hidden databases. In this paper, we investigate a interesting problem of 'breaking' the kNN restriction of such web databases to find more than k nearest point. To our best knowledge, this is the first work to study the problem over the kNN hidden database. We investigate and design a set of algorithms which can efficiently address this problem. Beyond that, we also perform a set of experiments over synthetic datasets and real-world datasets which illustrate the effectiveness of our algorithms.
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Document TypeConference paper
AffiliationUniversidade de Macau
Recommended Citation
GB/T 7714
Li H.,Gong Z.. Breaking the Top-κ Restriction of the kNN Hidden Databases[C],2017:302-307.
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