Modeling Uncertain Context Information via Event Probabilities

A.H. van Bunningen; L. Feng; Peter M.G. Apers

Modeling Uncertain Context Information via Event Probabilities

A.H. van Bunningen, L. Feng, Peter M.G. Apers

Databases (Former)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

1 Downloads (Pure)

Abstract

To be able to support context-awareness in an Ambient Intelligent (AmI) environment, one needs a way to model context. Previous research shows that a good way to model context is using Description Logics (DL). Since context data is often coming from sensors and therefore exhibits uncertain character, it is essential to take this uncertainty into account when exploiting and reasoning about context data. In this paper, we provide an event-based probabilistic method to model context uncertainty. Each context can be viewed as a probabilistic event, which can be either a basic or complex event. We show how to deal with correlations of events (i.e., inclusion, identicalness, disjunction, and independence) which are inherent in context data and investigate their in uences on the context uncertainty.

Original language	Undefined
Title of host publication	Proceedings of the 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases
Editors	Ander de Keijzer, A. de Keijzer, M. van Keulen, Maurice van Keulen
Place of Publication	Enschede, The Netherlands
Publisher	Centre for Telematics and Information Technology (CTIT)
Pages	25-32
Number of pages	8
Publication status	Published - 6 Jun 2006
Event	2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases, Enschede, The Netherlands: Proceedings of the 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases - Enschede, The Netherlands Duration: 6 Jun 2006 → …

Publication series

Name	CTIT Workshop Series
Publisher	Centre for Telematics and Information Technology University of Twente
Number	2
Volume	WP 06-01
ISSN (Print)	1574-0846
ISSN (Electronic)	0929-0672

Conference

Conference	2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases, Enschede, The Netherlands
City	Enschede, The Netherlands
Period	6/06/06 → …

Keywords

METIS-238258
EWI-7652
IR-63606
DB-CAQ: CONTEXT-AWARE QUERYING

Access to Document

Cite this

van Bunningen, A. H., Feng, L., & Apers, P. M. G. (2006). Modeling Uncertain Context Information via Event Probabilities. In A. de Keijzer, A. de Keijzer, M. van Keulen, & M. van Keulen (Eds.), Proceedings of the 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases (pp. 25-32). (CTIT Workshop Series; Vol. WP 06-01, No. 2). Centre for Telematics and Information Technology (CTIT). http://eprints.eemcs.utwente.nl/secure2/7652/01/paper04.pdf

van Bunningen, A.H. ; Feng, L. ; Apers, Peter M.G. / Modeling Uncertain Context Information via Event Probabilities. Proceedings of the 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases. editor / Ander de Keijzer ; A. de Keijzer ; M. van Keulen ; Maurice van Keulen. Enschede, The Netherlands : Centre for Telematics and Information Technology (CTIT), 2006. pp. 25-32 (CTIT Workshop Series; 2).

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abstract = "To be able to support context-awareness in an Ambient Intelligent (AmI) environment, one needs a way to model context. Previous research shows that a good way to model context is using Description Logics (DL). Since context data is often coming from sensors and therefore exhibits uncertain character, it is essential to take this uncertainty into account when exploiting and reasoning about context data. In this paper, we provide an event-based probabilistic method to model context uncertainty. Each context can be viewed as a probabilistic event, which can be either a basic or complex event. We show how to deal with correlations of events (i.e., inclusion, identicalness, disjunction, and independence) which are inherent in context data and investigate their in uences on the context uncertainty.",

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note = "Imported from EWI/DB PMS [db-utwente:inpr:0000003726]; 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases, Enschede, The Netherlands ; Conference date: 06-06-2006",

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van Bunningen, AH, Feng, L & Apers, PMG 2006, Modeling Uncertain Context Information via Event Probabilities. in A de Keijzer, A de Keijzer, M van Keulen & M van Keulen (eds), Proceedings of the 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases. CTIT Workshop Series, no. 2, vol. WP 06-01, Centre for Telematics and Information Technology (CTIT), Enschede, The Netherlands, pp. 25-32, 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases, Enschede, The Netherlands, Enschede, The Netherlands, 6/06/06. <http://eprints.eemcs.utwente.nl/secure2/7652/01/paper04.pdf>

Modeling Uncertain Context Information via Event Probabilities. / van Bunningen, A.H.; Feng, L.; Apers, Peter M.G.
Proceedings of the 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases. ed. / Ander de Keijzer; A. de Keijzer; M. van Keulen; Maurice van Keulen. Enschede, The Netherlands: Centre for Telematics and Information Technology (CTIT), 2006. p. 25-32 (CTIT Workshop Series; Vol. WP 06-01, No. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Modeling Uncertain Context Information via Event Probabilities

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AU - Feng, L.

AU - Apers, Peter M.G.

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PY - 2006/6/6

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AB - To be able to support context-awareness in an Ambient Intelligent (AmI) environment, one needs a way to model context. Previous research shows that a good way to model context is using Description Logics (DL). Since context data is often coming from sensors and therefore exhibits uncertain character, it is essential to take this uncertainty into account when exploiting and reasoning about context data. In this paper, we provide an event-based probabilistic method to model context uncertainty. Each context can be viewed as a probabilistic event, which can be either a basic or complex event. We show how to deal with correlations of events (i.e., inclusion, identicalness, disjunction, and independence) which are inherent in context data and investigate their in uences on the context uncertainty.

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BT - Proceedings of the 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases

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A2 - van Keulen, Maurice

PB - Centre for Telematics and Information Technology (CTIT)

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van Bunningen AH, Feng L, Apers PMG. Modeling Uncertain Context Information via Event Probabilities. In de Keijzer A, de Keijzer A, van Keulen M, van Keulen M, editors, Proceedings of the 2nd Twente Data Management Workshop (TDM'06) on Uncertainty in Databases. Enschede, The Netherlands: Centre for Telematics and Information Technology (CTIT). 2006. p. 25-32. (CTIT Workshop Series; 2).