Class-based conditional MaxRS query in spatial data streams

Mir Imtiaz Mostafiz, S. M.Farabi Mahmud, Muhammed Mas Ud Hussain, Mohammed Eunus Ali, Goce Trajcevski

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

1 Scopus citations

Abstract

We address the problem of maintaining the correct answer-sets to the Conditional Maximizing Range-Sum (C-MaxRS) query in spatial data streams. Given a set of (possibly weighted) 2D point objects, the traditional MaxRS problem determines an optimal placement for an axes-parallel rectangle r so that the number-or, the weighted sum-of objects in its interior is maximized. In many practical settings, the objects from a particular set-e.g., restaurants-can be of distinct types-e.g., fast-food, Asian, etc. The C-MaxRS problem deals with maximizing the overall sum, given class-based existential constraints, i.e., a lower bound on the count of objects of interests from particular classes. We first propose an efficient algorithm to the static C-MaxRS query, and extend the solution to handle dynamic (data streams) settings. Our experiments over datasets of up to 100,000 objects show that the proposed solutions provide significant efficiency benefits.

Original languageEnglish (US)
Title of host publicationSSDBM 2017
Subtitle of host publication29th International Conference on Scientific and Statistical Database Management
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450352826
DOIs
StatePublished - Jun 27 2017
Event29th International Conference on Scientific and Statistical Database Management, SSDBM 2017 - Chicago, United States
Duration: Jun 27 2017Jun 29 2017

Publication series

NameACM International Conference Proceeding Series
VolumePart F128636

Other

Other29th International Conference on Scientific and Statistical Database Management, SSDBM 2017
CountryUnited States
CityChicago
Period6/27/176/29/17

Keywords

  • C-MaxRS
  • Conditional MaxRS
  • Constrained query processing
  • Maximizing range sum query
  • Spatial data streams

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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