000 06699nam a22005895i 4500
001 978-3-642-13470-8
003 DE-He213
005 20140220084538.0
007 cr nn 008mamaa
008 100615s2010 gw | s |||| 0|eng d
020 _a9783642134708
_9978-3-642-13470-8
024 7 _a10.1007/978-3-642-13470-8
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
_2bisacsh
082 0 4 _a006.312
_223
100 1 _aBra, Paul.
_eeditor.
245 1 0 _aUser Modeling, Adaptation, and Personalization
_h[electronic resource] :
_b18th International Conference, UMAP 2010, Big Island, HI, USA, June 20-24, 2010. Proceedings /
_cedited by Paul Bra, Alfred Kobsa, David Chin.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2010.
300 _aXVIII, 428p. 115 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v6075
505 0 _aKeynote 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 Networks Implementation 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.
520 _aThis 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.
650 0 _aComputer science.
650 0 _aData mining.
650 0 _aInformation storage and retrieval systems.
650 0 _aInformation systems.
650 0 _aArtificial intelligence.
650 0 _aOptical pattern recognition.
650 1 4 _aComputer Science.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aInformation Systems Applications (incl.Internet).
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aUser Interfaces and Human Computer Interaction.
650 2 4 _aPattern Recognition.
700 1 _aKobsa, Alfred.
_eeditor.
700 1 _aChin, David.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642134692
830 0 _aLecture Notes in Computer Science,
_x0302-9743 ;
_v6075
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-13470-8
912 _aZDB-2-SCS
912 _aZDB-2-LNC
999 _c112266
_d112266