Efficiently and effectively finding window representatives

Lana Senyor-Schloss, Sara Cohen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Increasingly many applications leverage geographic data, and display this data to the user, e.g., to show sites of interest or friends in the vicinity. Given a window of interest, it is often advantageous to display only a bounded number k of representative points, instead of the entire contents of the window. This is helpful as a summary of the window contents. It is also quite necessary when the screen is small, and the window contains many points, as displaying all points will yield an incomprehensible output. This paper presents an approach to finding k representatives of a window. Unlike previous methods, which were based on fetching and clustering the relevant data, in this paper a method is presented for exploiting an existing indexing structure of the data to provide high quality results in efficient time, without explicitly accessing the data in the window. Experimental results prove that this new method for choosing representatives provides high quality results (i.e., comparable to fully clustering the data) while achieving significantly better runtime.

Original languageAmerican English
Title of host publicationProceedings of the 5th International Workshop on Mobile Entity Localization and Tracking in GPS-Less Environments, MELT 2015
EditorsYing Zhang, Bodhi Priyantha
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450339681
DOIs
StatePublished - 3 Nov 2015
Event5th International Workshop on Mobile Entity Localization and Tracking in GPS-Less Environments, MELT 2015 - Seattle, United States
Duration: 3 Nov 2015 → …

Publication series

NameProceedings of the 5th International Workshop on Mobile Entity Localization and Tracking in GPS-Less Environments, MELT 2015

Conference

Conference5th International Workshop on Mobile Entity Localization and Tracking in GPS-Less Environments, MELT 2015
Country/TerritoryUnited States
CitySeattle
Period3/11/15 → …

Bibliographical note

Publisher Copyright:
© 2015 ACM.

Keywords

  • Clustering
  • Representatives
  • Windows

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