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Interaction Analysis for Adaptive User Interfaces

Nazemi, Kawa and Stab, Christian and Fellner, Dieter W. (2010):
Interaction Analysis for Adaptive User Interfaces.
In: Lecture Notes in Computer Science (LNCS); 6215, pp. 362-371, Springer, Berlin, Heidelberg, New York, Advanced Intelligent Computing Theories and Applications, DOI: 10.1007/978-3-642-14922-1₄₅,
[Conference or Workshop Item]

Abstract

Adaptive User Interfaces are able to facilitate the handling of computer systems through the automatic adaptation to users' needs and preferences. For the realization of these systems, information about the individual user is needed. This user information can be extracted from user events by applying analytical methods without the active information input by the user. In this paper we introduce a reusable interaction analysis system based on probabilistic methods that predicts user interactions, recognizes user activities and detects user preferences on different levels of abstraction. The evaluation reveals that the prediction quality of the developed algorithm outperforms the quality of other established prediction methods.

Item Type: Conference or Workshop Item
Erschienen: 2010
Creators: Nazemi, Kawa and Stab, Christian and Fellner, Dieter W.
Title: Interaction Analysis for Adaptive User Interfaces
Language: English
Abstract:

Adaptive User Interfaces are able to facilitate the handling of computer systems through the automatic adaptation to users' needs and preferences. For the realization of these systems, information about the individual user is needed. This user information can be extracted from user events by applying analytical methods without the active information input by the user. In this paper we introduce a reusable interaction analysis system based on probabilistic methods that predicts user interactions, recognizes user activities and detects user preferences on different levels of abstraction. The evaluation reveals that the prediction quality of the developed algorithm outperforms the quality of other established prediction methods.

Series Name: Lecture Notes in Computer Science (LNCS); 6215
Publisher: Springer, Berlin, Heidelberg, New York
Uncontrolled Keywords: Interaction analysis, User modeling, Adaptive user interfaces, Probabilistic models, Adaptive information visualization
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: Advanced Intelligent Computing Theories and Applications
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1007/978-3-642-14922-1₄₅
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