Journal article

Maximizing Bichromatic Reverse Spatial and Textual k Nearest Neighbor Queries

Farhana M Choudhury, J Shane Culpepper, Timos Sellis, Xin Cao

PROCEEDINGS OF THE VLDB ENDOWMENT | ASSOC COMPUTING MACHINERY | Published : 2016

Abstract

The problem of maximizing bichromatic reverse k nearest neighbor queries (BRkNN) has been extensively studied in spatial databases. In this work, we present a related query for spatial-textual databases that finds an optimal location, and a set of keywords that maximizes the size of bichromatic reverse spatial textual k nearest neighbors (MaxBRSTkNN). Such a query has many practical applications including social media advertisements where a limited number of relevant advertisements are displayed to each user. The problem is to find the location and the text contents to include in an advertisement so that it will be displayed to the maximum number of users. The increasing availability of spat..

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Grants

Awarded by ARC Discovery Projects Scheme


Awarded by ARC DECRA Research Fellowship


Funding Acknowledgements

This work was supported by the ARC Discovery Projects Scheme (DP140101587). Shane Culpepper is the recipient of an ARC DECRA Research Fellowship (DE140100275). Farhana Choudhury is the recipient of a NICTA scholarship. We thank Chen et al. [1] for providing the IR-tree implementation. We thank the anonymous reviewers for their comments. An extended version of the paper is available in the first author's personal website that includes additional graphs and explanations as recommended by one of the reviewers.