User intent to support proactivity in a pervasive system

Yussuf Abu-Shaaban; Sarah McBurney; Nick Taylor; Morgan Howard Williams; Nikos Kalatzis; Ioanna Roussaki

User intent to support proactivity in a pervasive system

Yussuf Abu-Shaaban^*, Sarah McBurney, Nick Taylor, Morgan Howard Williams, Nikos Kalatzis, Ioanna Roussaki

^*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

In a pervasive system it is essential to understand the intent of the user in order to predict his/her future behaviour. This in turn will help to minimise the user's administrative overheads and assist the user to achieve his/her goals. The aim of this paper is to present some aspects of how user intent may be handled. It focuses on the architecture supporting the proactive features of the Persist pervasive platform. A formal definition of the task discovery problem in user intent is provided. The use of the discovered task model to predict the user's next intended task/action is introduced including the way in which user context can assist in the prediction of the user's intended task/action.

Original language	English
Title of host publication	Adaptive and Emergent Behaviour and Complex Systems
Subtitle of host publication	Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour
Publisher	Society for the Study of Artificial Intelligence and the Simulation of Behaviour
Pages	3-8
Number of pages	6
ISBN (Print)	1902956850, 9781902956855
Publication status	Published - 2009
Event	23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour 2009 - Edinburgh, United Kingdom Duration: 6 Apr 2009 → 9 Apr 2009

Conference

Conference	23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour 2009
Abbreviated title	AISB 2009
Country/Territory	United Kingdom
City	Edinburgh
Period	6/04/09 → 9/04/09

ASJC Scopus subject areas

Artificial Intelligence
Modelling and Simulation

Cite this

Abu-Shaaban, Y., McBurney, S., Taylor, N., Williams, M. H., Kalatzis, N., & Roussaki, I. (2009). User intent to support proactivity in a pervasive system. In Adaptive and Emergent Behaviour and Complex Systems: Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour (pp. 3-8). Society for the Study of Artificial Intelligence and the Simulation of Behaviour.

Abu-Shaaban, Yussuf ; McBurney, Sarah ; Taylor, Nick et al. / User intent to support proactivity in a pervasive system. Adaptive and Emergent Behaviour and Complex Systems: Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. Society for the Study of Artificial Intelligence and the Simulation of Behaviour, 2009. pp. 3-8

@inproceedings{e0ed5f55a7f64f01883af99bc878e297,

title = "User intent to support proactivity in a pervasive system",

abstract = "In a pervasive system it is essential to understand the intent of the user in order to predict his/her future behaviour. This in turn will help to minimise the user's administrative overheads and assist the user to achieve his/her goals. The aim of this paper is to present some aspects of how user intent may be handled. It focuses on the architecture supporting the proactive features of the Persist pervasive platform. A formal definition of the task discovery problem in user intent is provided. The use of the discovered task model to predict the user's next intended task/action is introduced including the way in which user context can assist in the prediction of the user's intended task/action.",

author = "Yussuf Abu-Shaaban and Sarah McBurney and Nick Taylor and Williams, {Morgan Howard} and Nikos Kalatzis and Ioanna Roussaki",

year = "2009",

language = "English",

isbn = "1902956850",

pages = "3--8",

booktitle = "Adaptive and Emergent Behaviour and Complex Systems",

publisher = "Society for the Study of Artificial Intelligence and the Simulation of Behaviour",

note = "23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour 2009, AISB 2009 ; Conference date: 06-04-2009 Through 09-04-2009",

}

Abu-Shaaban, Y, McBurney, S, Taylor, N, Williams, MH, Kalatzis, N & Roussaki, I 2009, User intent to support proactivity in a pervasive system. in Adaptive and Emergent Behaviour and Complex Systems: Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. Society for the Study of Artificial Intelligence and the Simulation of Behaviour, pp. 3-8, 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour 2009, Edinburgh, United Kingdom, 6/04/09.

User intent to support proactivity in a pervasive system. / Abu-Shaaban, Yussuf; McBurney, Sarah; Taylor, Nick et al.
Adaptive and Emergent Behaviour and Complex Systems: Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. Society for the Study of Artificial Intelligence and the Simulation of Behaviour, 2009. p. 3-8.

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

TY - GEN

T1 - User intent to support proactivity in a pervasive system

AU - Abu-Shaaban, Yussuf

AU - McBurney, Sarah

AU - Taylor, Nick

AU - Williams, Morgan Howard

AU - Kalatzis, Nikos

AU - Roussaki, Ioanna

PY - 2009

Y1 - 2009

N2 - In a pervasive system it is essential to understand the intent of the user in order to predict his/her future behaviour. This in turn will help to minimise the user's administrative overheads and assist the user to achieve his/her goals. The aim of this paper is to present some aspects of how user intent may be handled. It focuses on the architecture supporting the proactive features of the Persist pervasive platform. A formal definition of the task discovery problem in user intent is provided. The use of the discovered task model to predict the user's next intended task/action is introduced including the way in which user context can assist in the prediction of the user's intended task/action.

AB - In a pervasive system it is essential to understand the intent of the user in order to predict his/her future behaviour. This in turn will help to minimise the user's administrative overheads and assist the user to achieve his/her goals. The aim of this paper is to present some aspects of how user intent may be handled. It focuses on the architecture supporting the proactive features of the Persist pervasive platform. A formal definition of the task discovery problem in user intent is provided. The use of the discovered task model to predict the user's next intended task/action is introduced including the way in which user context can assist in the prediction of the user's intended task/action.

UR - http://www.scopus.com/inward/record.url?scp=84859071144&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:84859071144

SN - 1902956850

SN - 9781902956855

SP - 3

EP - 8

BT - Adaptive and Emergent Behaviour and Complex Systems

PB - Society for the Study of Artificial Intelligence and the Simulation of Behaviour

T2 - 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour 2009

Y2 - 6 April 2009 through 9 April 2009

ER -

Abu-Shaaban Y, McBurney S, Taylor N, Williams MH, Kalatzis N, Roussaki I. User intent to support proactivity in a pervasive system. In Adaptive and Emergent Behaviour and Complex Systems: Proceedings of the 23rd Convention of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. Society for the Study of Artificial Intelligence and the Simulation of Behaviour. 2009. p. 3-8

User intent to support proactivity in a pervasive system

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ASJC Scopus subject areas

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