Granular best match algorithm for context-aware computing systems

A. Baki Kocaballi*, Altan Koçyiǧit

*Corresponding author for this work

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

5 Citations (Scopus)


In order to be context-aware, a system or application should adapt its behavior according to current context, changing over time. Current context is acquired by some context provision mechanisms like sensors or other applications. After acquiring current context, this information should be matched against the previously defined context sets. In this paper, a granular best match algorithm dealing with the subjective, fuzzy, multi-granular and multi-dimensional characteristics of contextual information is introduced. The CAPRA - Context-Aware Personal Reminder Agent tool is used to show the applicability of the new context matching algorithm. The obtained outputs showed that proposed algorithm produces the results which are more sensitive to the user's intention, and more adaptive to the aforementioned characteristics of the contextual information than the traditional exact match method.

Original languageEnglish
Title of host publicationPERSER '06 Proceedings of the 2006 ACS/IEEE International Conference on Pervasive Services
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages7
ISBN (Print)1424402379, 9781424402373
Publication statusPublished - 1 Dec 2006
Externally publishedYes
EventICPS:2006 International Conference on Pervasive Services - Lyon, France
Duration: 26 Jun 200629 Jun 2006


ConferenceICPS:2006 International Conference on Pervasive Services


  • Context matching
  • Context-aware computing
  • Context-awareness
  • Pervasive computing


Dive into the research topics of 'Granular best match algorithm for context-aware computing systems'. Together they form a unique fingerprint.

Cite this