User Modeling, Adaptation, and Personalization

The 18th InternationalConference on User Modeling, Adaptation and Person- ization(UMAP 2010)took placeon BigIsland, HawaiiduringJune 20 24,2010. It was the second conference after UMAP 2009 in Trento, Italy, which merged the successful biannual User Modeling (UM) and Adaptive Hypermedia (AH) conference series. The ResearchPapertrackof the conferencewaschairedbyPaulDe Brafrom the Eindhoven University of Technology and Alfred Kobsa from the University ofCalifornia,Irvine. TheywereassistedbyaninternationalProgramCommittee of 80 leading ?gures in the AH and UM communities as well as highly promising youngerresearchers. Papersinthe ResearchPapertrackweregenerallyreviewed by three and sometimes even four reviewers, with one of them acting as a lead who initiates a discussion between reviewers and reconciles their opinions in a meta-review. The conferencesolicitedLong ResearchPapersof up to 12pagesin length, whichrepresentoriginalreports of substantivenew research. In addition, theconferenceacceptedShortResearchPapersofuptosixpagesinlength,whose merit was assessed more in terms of originality and importance than maturity and technical validation. The Research Paper track received 161 submission, with 112 in the long and 49 in the short paper category. Of these, 26 long and 6 short papers were accepted, resulting in an acceptance rate of 23. 2% for long papers and 19. 9% overall. Many authors of rejected papers were encouraged to resubmit to the Poster and Demo track of the conference. Following the example of UMAP 2009, the conference also had an Ind- try Paper track chaired by Bhaskar Mehta from Google, Zur ich, Switzerland and Kurt Partridge from PARC, Palo Alto, USA.

Klappentext

This book constitutes the proceedings of the Second International Conference on User Modeling, Adaptation, and Personalization, held on Big Island, HI, USA, in June 2010. This annual conference was merged from the biennial conference series User Modeling, UM, and the conference on Adaptive Hypermedia and Adaptive Web-Based Systems, AH. The 26 long papers and 6 short papers presented together with 7 doctoral consortium papers, 2 invited talks, and 4 industry panel papers were carefully reviewed and selected from 161 submissions. The tutorials and workshops were organized in topical sections on intelligent techniques for web personalization and recommender systems; pervasive user modeling and personalization; user models for motivational systems; adaptive collaboration support; architectures and building blocks of web-based user adaptive systems; adaptation and personalization in e-b/learning using pedagogic conversational agents; and user modeling and adaptation for daily routines.

Inhalt
Keynote Speakers.- Modeling Emotion and Its Expression in Virtual Humans.- AdHeat An Influence-Based Diffusion Model for Propagating Hints to Personalize Social Ads.- Full Research Papers.- Can Concept-Based User Modeling Improve Adaptive Visualization?.- Interweaving Public User Profiles on the Web.- Modeling Long-Term Search Engine Usage.- Analysis of Strategies for Building Group Profiles.- Contextual Slip and Prediction of Student Performance after Use of an Intelligent Tutor.- Working Memory Span and E-Learning: The Effect of Personalization Techniques on Learners' Performance.- Scaffolding Self-directed Learning with Personalized Learning Goal Recommendations.- Instructional Video Content Employing User Behavior Analysis: Time Dependent Annotation with Levels of Detail.- A User-and Item-Aware Weighting Scheme for Combining Predictive User Models.- PersonisJ: Mobile, Client-Side User Modelling.- Twitter, Sensors and UI: Robust Context Modeling for Interruption Management.- Ranking Feature Sets for Emotion Models Used in Classroom Based Intelligent Tutoring Systems.- Inducing Effective Pedagogical Strategies Using Learning Context Features.- Yes!: Using Tutor and Sensor Data to Predict Moments of Delight during Instructional Activities.- A Personalized Graph-Based Document Ranking Model Using a Semantic User Profile.- Interaction and Personalization of Criteria in Recommender Systems.- Collaborative Inference of Sentiments from Texts.- User Modelling for Exclusion and Anomaly Detection: A Behavioural Intrusion Detection System.- IntrospectiveViews: An Interface for Scrutinizing Semantic User Models.- Analyzing Community Knowledge Sharing Behavior.- A Data-Driven Technique for Misconception Elicitation.- Modeling Individualization in a Bayesian NetworksImplementation of Knowledge Tracing.- Detecting Gaming the System in Constraint-Based Tutors.- Bayesian Credibility Modeling for Personalized Recommendation in Participatory Media.- A Study on User Perception of Personality-Based Recommender Systems.- Compass to Locate the User Model I Need: Building the Bridge between Researchers and Practitioners in User Modeling.- Industry Papers.- myCOMAND Automotive User Interface: Personalized Interaction with Multimedia Content Based on Fuzzy Preference Modeling.- User Modeling for Telecommunication Applications: Experiences and Practical Implications.- Mobile Web Profiling: A Study of Off-Portal Surfing Habits of Mobile Users.- Personalized Implicit Learning in a Music Recommender System.- Short Research Papers.- Personalised Pathway Prediction.- Towards a Customization of Rating Scales in Adaptive Systems.- Eye-Tracking Study of User Behavior in Recommender Interfaces.- Recommending Food: Reasoning on Recipes and Ingredients.- Disambiguating Search by Leveraging a Social Context Based on the Stream of User's Activity.- Features of an Independent Open Learner Model Influencing Uptake by University Students.- Doctoral Consortium Papers.- Recognizing and Predicting the Impact on Human Emotion (Affect) Using Computing Systems.- Utilising User Texts to Improve Recommendations.- Semantically-Enhanced Ubiquitous User Modeling.- User Modeling Based on Emergent Domain Semantics.- Biographic spaces: A Personalized Smoking Cessation Intervention in Second Life.- Task-Based User Modelling for Knowledge Work Support.- Enhancing User Interaction in Virtual Environments through Adaptive Personalized 3D Interaction Techniques.