Affective User Modeling for Adaptive Intelligent User Interfaces Export

@incollection{citeulike:2828562, abstract = {In this paper we describe the User Modeling phase of our general research approach: developing Adaptive Intelligent User Interfaces to facilitate enhanced natural communication during the Human-Computer Interaction. Natural communication is established by recognizing users' affective states (i.e., emotions experienced by the users) and responding to those emotions by adapting to the current situation via an affective user model. Adaptation of the interface was designed to provide multi-modal feedback to the users about their current affective state and to respond to users' negative emotional states in order to compensate for the possible negative impacts of those emotions. Bayesian Belief Networks formalization was employed to develop the User Model to enable the intelligent system to appropriately adapt to the current context and situation by considering user-dependent factors, such as: personality traits and preferences.}, author = {Nasoz, Fatma and Lisetti, Christine}, citeulike-article-id = {2828562}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-540-73110-8_45}, doi = {10.1007/978-3-540-73110-8_45}, journal = {Human-Computer Interaction. HCI Intelligent Multimodal Interaction Environments}, keywords = {adaptive, affective, bayesian, computing, network}, pages = {421--430}, posted-at = {2008-05-25 04:19:23}, priority = {0}, title = {Affective User Modeling for Adaptive Intelligent User Interfaces}, url = {http://dx.doi.org/10.1007/978-3-540-73110-8_45}, year = {2007} }

TY - CHAP ID - citeulike:2828562 L3 - citeulike-article-id:2828562 N2 - In this paper we describe the User Modeling phase of our general research approach: developing Adaptive Intelligent User Interfaces to facilitate enhanced natural communication during the Human-Computer Interaction. Natural communication is established by recognizing users’ affective states (i.e., emotions experienced by the users) and responding to those emotions by adapting to the current situation via an affective user model. Adaptation of the interface was designed to provide multi-modal feedback to the users about their current affective state and to respond to users’ negative emotional states in order to compensate for the possible negative impacts of those emotions. Bayesian Belief Networks formalization was employed to develop the User Model to enable the intelligent system to appropriately adapt to the current context and situation by considering user-dependent factors, such as: personality traits and preferences. JF - Human-Computer Interaction. HCI Intelligent Multimodal Interaction Environments EP - 430 TI - Affective User Modeling for Adaptive Intelligent User Interfaces SP - 421 KW - adaptive KW - affective KW - bayesian KW - computing KW - network AU - Nasoz, Fatma AU - Lisetti, Christine PY - 2007/// UR - http://dx.doi.org/10.1007/978-3-540-73110-8_45 ER -