Human activity inference using hierarchical Bayesian network in mobile contexts

Young Seol Lee, Sung Bae Cho

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

7 Citations (Scopus)

Abstract

Since smart phones with diverse functionalities become the general trend, many context-aware services have been studied and launched. The services exploit a variety of contextual information in the mobile environment. Even though it has attempted to infer activities using a mobile device, it is difficult to infer human activities from uncertain, incomplete and insufficient mobile contextual information. We present a method to infer a person's activities from mobile contexts using hierarchically structured Bayesian networks. Mobile contextual information collected for one month is used to evaluate the method. The results show the usefulness of the proposed method.

Original languageEnglish
Title of host publicationNeural Information Processing - 18th International Conference, ICONIP 2011, Proceedings
Pages38-45
Number of pages8
EditionPART 1
DOIs
Publication statusPublished - 2011 Nov 28
Event18th International Conference on Neural Information Processing, ICONIP 2011 - Shanghai, China
Duration: 2011 Nov 132011 Nov 17

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume7062 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other18th International Conference on Neural Information Processing, ICONIP 2011
CountryChina
CityShanghai
Period11/11/1311/11/17

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Lee, Y. S., & Cho, S. B. (2011). Human activity inference using hierarchical Bayesian network in mobile contexts. In Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings (PART 1 ed., pp. 38-45). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7062 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-24955-6_5