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Advances in User Modeling

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Cover of 'Advances in User Modeling'

Table of Contents

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    Book Overview
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    Chapter 1 Adaptive Support for Team Collaboration
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    Chapter 2 A Visualization Model Supporting an Efficient Context Resumption in Collaboration Environments
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    Chapter 3 Scaffolding Collaborative Learning Opportunities: Integrating Microworld Use and Argumentation
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    Chapter 4 Augmenting User Models with Real World Experiences to Enhance Personalization and Adaptation
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    Chapter 5 The Personal Adaptive In-Car HMI: Integration of External Applications for Personalized Use
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    Chapter 6 Core Aspects of Affective Metacognitive User Models
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    Chapter 7 Recommender Systems and the Social Web
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    Chapter 8 Identifying Relevant YouTube Comments to Derive Socially Augmented User Models: A Semantically Enriched Machine Learning Approach
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    Chapter 9 Decision Making and Recommendation Acceptance Issues in Recommender Systems
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    Chapter 10 Designing an Explanation Interface for Proactive Recommendations in Automotive Scenarios
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    Chapter 11 Group Decision Support for Requirements Negotiation
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    Chapter 12 Personalization Approaches in Learning Environments
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    Chapter 13 A Procedure to Automatically Adapt Questions in Student – Pedagogic Conversational Agent Dialogues
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    Chapter 14 Modelling Empathy in Social Robotic Companions
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    Chapter 15 Understanding Student Attention to Adaptive Hints with Eye-Tracking
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    Chapter 16 Psycho-pedagogical Mash-Up Design for Personalising the Learning Environment
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    Chapter 17 Semantic Adaptive Social Web
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    Chapter 18 Semantic Disambiguation and Contextualisation of Social Tags
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    Chapter 19 Folkview: A Multi-agent System Approach to Modeling Folksonomies
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    Chapter 20 Selective Propagation of Social Data in Decentralized Online Social Network
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    Chapter 21 Trust, Reputation and User Modeling
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    Chapter 22 Recommending Services in a Trust-Based Decentralized User Modeling System
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    Chapter 23 Building Trust Communities Using Social Trust
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    Chapter 24 Improving Access Control for Mobile Consumers of Services by Use of Context and Trust within the Call-Stack
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    Chapter 25 The Influence of Interaction Attributes on Trust in Virtual Communities
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    Chapter 26 Decision Making and Recommendation Protocol Based on Trust for Multi-agent Systems
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    Chapter 27 Handling Subjective User Feedback for Reputation Computation in Virtual Reality
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    Chapter 28 User Modeling and Adaptation for Daily Routines: Providing Assistance to People with Special and Specific Needs
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    Chapter 29 Guiding Patients in the Hospital
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    Chapter 30 Supportive Adaptive User Interfaces Inside and Outside the Home
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    Chapter 31 User Models for Motivational Systems
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    Chapter 32 Impact of Implicit and Explicit Affective Labeling on a Recommender System’s Performance
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    Chapter 33 Arguing about Emotion
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    Chapter 34 Motivating People in Smart Environments
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    Chapter 35 Towards Adaptive Recruitment and Engagement Mechanisms in Social Systems
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    Chapter 36 Towards a New Dimension for User Modeling: The Use of Sensory Vocabulary
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    Chapter 37 SERUM: Collecting Semantic User Behavior for Improved News Recommendations
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    Chapter 38 INGRID: A Web Service Tool for Hierarchical Open Learner Model Visualization
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    Chapter 39 An Acceptance Model of Recommender Systems Based on a Large-Scale Internet Survey
Overall attention for this book and its chapters
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Title
Advances in User Modeling
Published by
Springer Science & Business Media, February 2012
DOI 10.1007/978-3-642-28509-7
ISBNs
978-3-64-228508-0, 978-3-64-228509-7
Editors

Ardissono, Liliana, Kuflik, Tsvi, Ardissono, Liliana, Kuflik, Tsvi

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 1 2%
Student > Postgraduate 1 2%
Unknown 57 97%
Readers by discipline Count As %
Computer Science 2 3%
Unknown 57 97%