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

Contributor(s): Material type: TextTextPublication details: Cambridge, United Kingdom : Cambridge University Press, c2022Description: xii, 360 pages : illustrations ; 24 cmISBN:
  • 9781108792707
Subject(s): LOC 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 Call number Copy number Status Date due Barcode
Books Books National University - Manila LRC - Graduate Studies General Circulation Doctor in Information Technology 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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