ORange: Objective-Aware Range Query Refinement

Abdullah Albarrak, Tatiana Noboa, Hina A. Khan, Mohamed A. Sharaf, Xiaofang Zhou, Shazia Sadiq

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

In this demo paper we present Orange, a system prototype for objective-aware range query refinement. Orange essentially refines a range query to meet a pre-specified cardinality constraint while taking into account the (dis)similarity between the initial query and its corresponding refined version. To achieve this goal, Orange employes the novel scheme SAQR for efficient similarity-aware query refinement. The main idea underlying SAQR is to utilize the pre-defined constraints on cardinality and similarity in order to bound the search space and quickly find a refined query, which meets the user's expectations. We showcase Orange in a web-based application which aims to guide planners in allocating service zones for police patrol units using real and historical dataset of crime incidents.

Original languageEnglish
Title of host publicationProceedings - 2014 IEEE 15th International Conference on Mobile Data Management, IEEE MDM 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages333-336
Number of pages4
ISBN (Electronic)9781479957057
DOIs
Publication statusPublished - Oct 5 2014
Externally publishedYes
Event15th IEEE International Conference on Mobile Data Management, IEEE MDM 2014 - Brisbane, Australia
Duration: Jul 15 2014Jul 18 2014

Publication series

NameProceedings - IEEE International Conference on Mobile Data Management
Volume1
ISSN (Print)1551-6245

Conference

Conference15th IEEE International Conference on Mobile Data Management, IEEE MDM 2014
Country/TerritoryAustralia
CityBrisbane
Period7/15/147/18/14

ASJC Scopus subject areas

  • General Engineering

Fingerprint

Dive into the research topics of 'ORange: Objective-Aware Range Query Refinement'. Together they form a unique fingerprint.

Cite this