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Bayesian methods for interaction and design / edited by John H. Williamson [and three others].

Contributor(s): Williamson, John H [editor] | Oulasvirta, Antti [editor] | Kristensson, Per Ola [editor] | Banovic, Nikola [editor]Material type: Text

TextPublication details: Cambridge, United Kingdom : Cambridge University Press, c2022Description: xii, 360 pages : illustrations ; 24 cmISBN: 9781108792707Subject(s): HUMAN ENGINEERING -- MATHEMATICSLOC classification: TA 167 .B39 2022

Contents:

Bayseian statistics / A. Dix -- Bayseian information gain to design interaction / W. Liu, O. Rioul, M Beaudouin-Lafon -- Bayseian command selection / S. Zhu, X. Fan, F. Tian, X. Bi.

Summary: Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers.

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Item type	Current library	Home library	Collection	Shelving location	Call number	Copy number	Status	Date due	Barcode
Books	LRC - Graduate Studies	National University - Manila	Doctor in Information Technology	General Circulation	GC TA 167 .B39 2022 (Browse shelf (Opens below))	c.1	Available		NULIB000019292

Bayseian statistics / A. Dix --
Bayseian information gain to design interaction / W. Liu, O. Rioul, M Beaudouin-Lafon --
Bayseian command selection / S. Zhu, X. Fan, F. Tian, X. Bi.

Intended for researchers and practitioners in interaction design, this book shows how Bayesian models can be brought to bear on problems of interface design and user modelling. It introduces and motivates Bayesian modelling and illustrates how powerful these ideas can be in thinking about human-computer interaction, especially in representing and manipulating uncertainty. Bayesian methods are increasingly practical as computational tools to implement them become more widely available, and offer a principled foundation to reason about interaction design. The book opens with a self-contained tutorial on Bayesian concepts and their practical implementation, tailored for the background and needs of interaction designers.

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