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Maximizing bichromatic reverse spatial and textual k nearest neighbor queries

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posted on 2024-07-09, 19:54 authored by Farhana M. Choudhury, J. Shane Culpepper, Timos Sellis, Xin Cao
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 spatial-textual collections allows us to answer these queries for both spatial proximity and textual similarity. This paper is the first to consider the MaxBRSTkNN query. We show that the problem is NP-hard and present both approximate and exact solutions.

Funding

FEASIBILITY AND ECONOMIC IMPACT BASED CLUSTER DEVELOPMENT FOR AGRIBUSINESS AND OTHER APPROPRIATE ACTIVITY

National Institute of Food and Agriculture

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Molecular Discriminators in Benign Breast Tissue for Future Risk of ER positive a

National Cancer Institute

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ISSN

2150-8097

Journal title

Proceedings of the VLDB Endowment

Volume

9

Issue

6

Pagination

11 pp

Publisher

VLDB Endowment

Copyright statement

Copyright © 2016 VLDB Endowment. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/. For any use beyond those covered by this license, obtain permission by emailing info@vldb.org.

Language

eng

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