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User modeling

About: User modeling is a research topic. Over the lifetime, 10701 publications have been published within this topic receiving 278012 citations.


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Journal ArticleDOI
TL;DR: In this paper, the goal of a tool is to "serve" the user in the context of the task it is intended for, and every tool should feel like it was custom designed for that user.
Abstract: People use tools to achieve desired results. Goal-directed behavior is a human characteristic. While in rare instances someone might speak of being "guided" by tools, we do not generally think of tools as having goals. We would like our tools to be able to suggest what they are for (in the words of Norman [3], to offer affordances), but we do not expect them to control what we do. We hope to provide craftsmen with tools that enable them to engage in conversations with their materials. In an ideal world, the mantra for our tools would be "My purpose is to serve you." Every tool should feel like it was custom designed for you, the user in your context.

80 citations

Journal ArticleDOI
TL;DR: A method for responding to misconceptions in a domain-independent and context-sensitive fashion is discussed, which calls for reasoning about possible sources of the misconception using a model of the user and generating a response based on this reasoning.

80 citations

Proceedings ArticleDOI
16 Oct 2010
TL;DR: Results of the evaluation indicate the technique's robustness for user identification within small groups, and a set of interaction techniques are introduced to illustrate how HandsDown can improve the user experience.
Abstract: HandsDown is a novel technique for user identification on interactive surfaces. It enables users to access personal data on a shared surface, to associate objects with their identity, and to fluidly customize appearance, content, or functionality of the user interface. To identify, users put down their hand flat on the surface. HandsDown is based on hand contour analysis; neither user instrumentation nor external devices are required for identification. Characteristic features of the hand are initially extracted from images captured by the surface's camera system and then classified using Support Vector Machines (SVM).We present a proof-of-concept implementation and show results of our evaluation which indicates the technique's robustness for user identification within small groups. Additionally, we introduce a set of interaction techniques to illustrate how HandsDown can improve the user experience, and we discuss the design space of such interactions.

80 citations

Journal ArticleDOI
TL;DR: In this article, a decision support framework that assists the development of emotionally appealing products by eliciting user needs early in the development process has been developed and validated through industrial case studies.
Abstract: Affective design quantifies user reactions and defines their relationship to physical parameters of designs. This knowledge can inform the generation of better interfaces between product and user and can increase the product appeal in both mature and new markets. This study presents a decision support framework that assists the development of emotionally appealing products by eliciting user needs early in the development process. It has been developed and validated through industrial case studies. Some aspects of the approach have evolved from Kansei engineering but the fields of linguistics, engineering and psychology have contributed further functionality and user support. The framework can be adopted at any stage early in the product development process to provide guidelines for optimising the emotional product communication. The framework embodies methods for adjective selection, concept definition, user experiments and quantitative user evaluations. Using these, the practitioner can select the range ...

80 citations

Proceedings ArticleDOI
27 Nov 2001
TL;DR: The use of memory tools to detect missing effects and CIS sequences is investigated, investigating interactions between CIS sequences, and empirical studies of five different GUI systems are provided.
Abstract: Testing graphical user interfaces (GUIs) is difficult, involving many states, inputs and events. We have previously reported a new method for testing GUIs that is scalable and concentrates on user sequences of GUI objects and selections that collaborate, called complete interaction sequences (CIS) and that produce the desired response for the user called the responsibility. In this paper we extend this approach by investigating the use of memory tools to detect missing effects and CIS sequences, investigating interactions between CIS sequences, and providing empirical studies of five different GUI systems.

80 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202327
202269
2021150
2020167
2019194
2018216