Human activity inference using hierarchical Bayesian network in mobile contexts

Young Seol Lee; Sung Bae Cho

doi:10.1007/978-3-642-24955-6_5

Human activity inference using hierarchical Bayesian network in mobile contexts

Young Seol Lee, Sung Bae Cho

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings
Pages	38-45
Number of pages	8
Edition	PART 1
DOIs	https://doi.org/10.1007/978-3-642-24955-6_5
Publication status	Published - 2011 Nov 28
Event	18th International Conference on Neural Information Processing, ICONIP 2011 - Shanghai, China Duration: 2011 Nov 13 → 2011 Nov 17

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	7062 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	18th International Conference on Neural Information Processing, ICONIP 2011
Country	China
City	Shanghai
Period	11/11/13 → 11/11/17

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-642-24955-6_5

Fingerprint Dive into the research topics of 'Human activity inference using hierarchical Bayesian network in mobile contexts'. Together they form a unique fingerprint.

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

Lee, Young Seol ; Cho, Sung Bae. / Human activity inference using hierarchical Bayesian network in mobile contexts. Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 1. ed. 2011. pp. 38-45 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{50b6ca9ee54649a6960a56bffe9758f5,

title = "Human activity inference using hierarchical Bayesian network in mobile contexts",

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.",

author = "Lee, {Young Seol} and Cho, {Sung Bae}",

year = "2011",

month = nov,

day = "28",

doi = "10.1007/978-3-642-24955-6_5",

language = "English",

isbn = "9783642249549",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

number = "PART 1",

pages = "38--45",

booktitle = "Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings",

edition = "PART 1",

note = "18th International Conference on Neural Information Processing, ICONIP 2011 ; Conference date: 13-11-2011 Through 17-11-2011",

}

Lee, YS & Cho, SB 2011, Human activity inference using hierarchical Bayesian network in mobile contexts. in Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 7062 LNCS, pp. 38-45, 18th International Conference on Neural Information Processing, ICONIP 2011, Shanghai, China, 11/11/13. https://doi.org/10.1007/978-3-642-24955-6_5

Human activity inference using hierarchical Bayesian network in mobile contexts. / Lee, Young Seol; Cho, Sung Bae.

Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 1. ed. 2011. p. 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).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Human activity inference using hierarchical Bayesian network in mobile contexts

AU - Lee, Young Seol

AU - Cho, Sung Bae

PY - 2011/11/28

Y1 - 2011/11/28

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=81855172112&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=81855172112&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-24955-6_5

DO - 10.1007/978-3-642-24955-6_5

M3 - Conference contribution

AN - SCOPUS:81855172112

SN - 9783642249549

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 38

EP - 45

BT - Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings

T2 - 18th International Conference on Neural Information Processing, ICONIP 2011

Y2 - 13 November 2011 through 17 November 2011

ER -

Lee YS, Cho SB. Human activity inference using hierarchical Bayesian network in mobile contexts. In Neural Information Processing - 18th International Conference, ICONIP 2011, Proceedings. PART 1 ed. 2011. p. 38-45. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). https://doi.org/10.1007/978-3-642-24955-6_5