Abstract is missing.
- After Twenty-Five Years of User Modeling and Adaptation...What Makes us UMAP?Paul De Bra. 1 [doi]
- I'll be Watching You: Policing the Line between Personalization and PrivacyJennifer Golbeck. 2 [doi]
- Emotion Analysis in Natural LanguagePearl Pu. 3 [doi]
- Nudge your Workforce: A Study on the Effectiveness of Task Notification Strategies in Enterprise Mobile CrowdsourcingSarah Bashirieh, Sepideh Mesbah, Judith Redi, Alessandro Bozzon, Zoltán Szlávik, Robert-Jan Sips. 4-12 [doi]
- Long and Short-Term Recommendations with Recurrent Neural NetworksRobin Devooght, Hugues Bersini. 13-21 [doi]
- Using Learning Analytics to Devise Interactive Personalised Nudges for Active Video WatchingVania Dimitrova, Antonija Mitrovic, Alicja Piotrkowicz, Lydia Lau, Amali Weerasinghe. 22-31 [doi]
- A Multi-Armed Bandit Model Selection for Cold-Start User RecommendationCrícia Z. Felício, Klérisson V. R. Paixão, Célia A. Zorzo Barcelos, Philippe Preux. 32-40 [doi]
- Fine-Grained Open Learner Models: Complexity Versus SupportJulio D. Guerra-Hollstein, Jordan Barria-Pineda, Christian D. Schunn, Susan Bull, Peter Brusilovsky. 41-49 [doi]
- Where To Go Next?: Exploiting Behavioral User Models in Smart EnvironmentsSeyyed Hadi Hashemi, Jaap Kamps. 50-58 [doi]
- A New Statistical Density Clustering Algorithm based on Mutual Vote and Subjective Logic Applied to Recommender SystemsCharif Haydar, Anne Boyer. 59-66 [doi]
- RouteMe: A Mobile Recommender System for Personalized, Multi-Modal Route PlanningDaniel Herzog, Hesham Massoud, Wolfgang Wörndl. 67-75 [doi]
- Stereotype Modeling for Problem-Solving Performance Predictions in MOOCs and Traditional CoursesRoya Hosseini, Peter Brusilovsky, Michael Yudelson, Arto Hellas. 76-84 [doi]
- Learner Modeling for Integration SkillsYun Huang, Julio D. Guerra-Hollstein, Jordan Barria-Pineda, Peter Brusilovsky. 85-93 [doi]
- "Out of the Fr-Eye-ing Pan": Towards Gaze-Based Models of Attention during Learning with Technology in the ClassroomStephen Hutt, Caitlin Mills, Nigel Bosch, Kristina Krasich, James Brockmole, Sidney K. D'Mello. 94-103 [doi]
- Probabilistic Perspectives on Collecting Human Uncertainty in Predictive Data MiningKevin Jasberg, Sergej Sizov. 104-112 [doi]
- User Perception of Next-Track Music RecommendationsIman Kamehkhosh, Dietmar Jannach. 113-121 [doi]
- "Personal Social Dashboard": A Tool for Measuring Your Social Engagement Effectiveness in the EnterpriseShiri Kremer-Davidson, Inbal Ronen, Avi Kaplan, Maya Barnea. 122-130 [doi]
- Adaptive City Characteristics: How Location Familiarity Changes What Is Regionally DescriptiveVikas Kumar, Saeideh Bakhshi, Lyndon Kennedy, David A. Shamma. 131-139 [doi]
- Investigating the Impact of Personality and Cognitive Efficiency on the Selection of Exercises for LearnersJuliet Okpo, Judith Masthoff, Matt Dennis, Nigel A. Beacham, Ana Ciocarlan. 140-147 [doi]
- Imputing KCs with Representations of Problem Content and ContextZachary A. Pardos, Anant Dadu. 148-155 [doi]
- Experimental Analysis of Mastery Learning CriteriaRadek Pelánek, Jirí Rihák. 156-163 [doi]
- Using Eye Gaze Data and Visual Activities to Infer Human Cognitive Styles: Method and Feasibility StudiesGeorge E. Raptis, Christina P. Katsini, Marios Belk, Christos Fidas, George Samaras, Nikolaos M. Avouris. 164-173 [doi]
- Group Recommendations by Learning Rating BehaviorDimitris Sacharidis. 174-182 [doi]
- Let's Dance: How to Build a User Model for Dance Students Using Wearable TechnologyAugusto Dias Pereira dos Santos, Kalina Yacef, Roberto Martínez Maldonado. 183-191 [doi]
- Enhancing Student Models in Game-based Learning with Facial Expression RecognitionRobert Sawyer, Andy Smith, Jonathan P. Rowe, Roger Azevedo, James C. Lester. 192-201 [doi]
- A Deep Architecture for Content-based Recommendations Exploiting Recurrent Neural NetworksAlessandro Suglia, Claudio Greco 0002, Cataldo Musto, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro. 202-211 [doi]
- Measuring Student Behaviour Dynamics in a Large Interactive Classroom SettingVasileios Triglianos, Sambit Praharaj, Cesare Pautasso, Alessandro Bozzon, Claudia Hauff. 212-220 [doi]
- Inferring Contextual Preferences Using Deep Auto-EncodingMoshe Unger, Bracha Shapira, Lior Rokach, Ariel Bar. 221-229 [doi]
- Weighted Random Walk Sampling for Multi-Relational RecommendationFatemeh Vahedian, Robin D. Burke, Bamshad Mobasher. 230-237 [doi]
- Inferring Students' Sense of Community from Their Communication Behavior in Online CoursesWen Wu, Li Chen, Qingchang Yang. 238-246 [doi]
- Towards a Long Term Model of Virtual Reality Exergame ExertionSooJeong Yoo, Tristan Heywood, Lie Ming Tang, Bob Kummerfeld, Judy Kay. 247-255 [doi]
- Get to the Bottom: Causal Analysis for User ModelingShi Zong, Branislav Kveton, Shlomo Berkovsky, Azin Ashkan, Zheng Wen. 256-264 [doi]
- Interactive Prior Elicitation of Feature Similarities for Small Sample Size PredictionHomayun Afrabandpey, Tomi Peltola, Samuel Kaski. 265-269 [doi]
- An Analysis on Time- and Session-aware Diversification in Recommender SystemsVito Walter Anelli, Vito Bellini, Tommaso Di Noia, Wanda La Bruna, Paolo Tomeo, Eugenio Di Sciascio. 270-274 [doi]
- Deriving Item Features Relevance from Past User InteractionsLeonardo Cella, Stefano Cereda, Massimo Quadrana, Paolo Cremonesi. 275-279 [doi]
- A Clustering Approach for Personalizing Diversity in Collaborative Recommender SystemsFarzad Eskandanian, Bamshad Mobasher, Robin Burke. 280-284 [doi]
- Personality Traits and Music Genres: What Do People Prefer to Listen To?Bruce Ferwerda, Marko Tkalcic, Markus Schedl. 285-288 [doi]
- Improving Cold Start Recommendation by Mapping Feature-Based Preferences to Item ComparisonsSaikishore Kalloori, Francesco Ricci. 289-293 [doi]
- The Force Within: Recommendations Via Gravitational Attraction Between ItemsVikas Kumar, Saeideh Bakhshi, Lyndon Kennedy, David A. Shamma. 294-297 [doi]
- Encoding User as More Than the Sum of Their Parts: Recurrent Neural Networks and Word Embedding for People-to-people RecommendationAntoine Lefebvre-Brossard, Alexandre Spaeth, Michel C. Desmarais. 298-302 [doi]
- Multilingual Search User Behaviors - Exploring Multilingual Querying and Result Selection Through CrowdsourcingRyan Lowe, Ben Steichen. 303-307 [doi]
- Modelling Embodied Mobility Teamwork Strategies in a Simulation-Based Healthcare ClassroomRoberto Martínez Maldonado, Mykola Pechenizkiy, Simon Buckingham Shum, Tamara Power, Carolyn Hayes, Carmen Axisa. 308-312 [doi]
- Providing Control and Transparency in a Social Recommender System for Academic ConferencesChun-Hua Tsai, Peter Brusilovsky. 313-317 [doi]
- Towards Improving E-commerce Users Experience Using Personalization & Persuasive TechnologyIfeoma Adaji. 318-321 [doi]
- Analyzing the Impact of Social Connections on Rating Behavior in Social Recommender SystemsCarine Pierrette Mukamakuza. 322-326 [doi]
- Personalized Research Paper Recommendation using Deep LearningHebatallah A. Mohamed Hassan. 327-330 [doi]
- Conversational Group Recommender SystemsThuy Ngoc Nguyen. 331-334 [doi]
- Smart Technology for Supporting Dance EducationAugusto Dias Pereira dos Santos. 335-338 [doi]
- Harnessing Virtual Reality Exergames and Physical Fitness Sensing to Create a Personalised Game and DashboardSooJeong Yoo. 339-342 [doi]
- Modelling User Behaviour based on ProcessMengdie Zhuang. 343-346 [doi]
- Recommender Systems as Multistakeholder EnvironmentsHiman Abdollahpouri, Robin Burke, Bamshad Mobasher. 347-348 [doi]
- Towards Understanding Users' Motivation in a Q&A Social Network Using Social Influence and the Moderation by CultureIfeoma Adaji, Julita Vassileva. 349-350 [doi]
- Harvesting Entity-relation Social Networks from the Web: Potential and ChallengesSaeed Amal, Tsvi Kuflik, Einat Minkov. 351-352 [doi]
- Enhancing Collaborative Filtering with Friendship InformationLiliana Ardissono, Maurizio Ferrero, Giovanna Petrone, Marino Segnan. 353-354 [doi]
- Combining Supervised and Unsupervised Learning to Discover Emotional ClassesMiguel Arevalillo-Herráez, Aladdin Ayesh, Olga C. Santos, Pablo Arnau-González. 355-356 [doi]
- The Adaptation of an Individual's Satisfaction to Group Context: the Role of Ties Strength and ConflictsFrancesco Barile, Judith Masthoff, Silvia Rossi. 357-358 [doi]
- The Influence of City Size on Dietary Choices and Food RecommendationHao Cheng, Markus Rokicki, Eelco Herder. 359-360 [doi]
- Behavioral Patterns Mining for Online Time PersonalizationTomas Chovanak, Ondrej Kassák, Mária Bieliková. 361-362 [doi]
- Modeling the Dynamics of Online News Reading InterestsElena Viorica Epure, Benjamin Kille, Jon Espen Ingvaldsen, Rébecca Deneckère, Camille Salinesi, Sahin Albayrak. 363-364 [doi]
- User Verification on Mobile Devices Using Sequences of Touch GesturesLiron Ben Kimon, Yisroel Mirsky, Lior Rokach, Bracha Shapira. 365-366 [doi]
- User Modeling for the Internet of ThingsBob Kummerfeld, Judy Kay. 367-368 [doi]
- Impact of Individual Differences on User Experience with a Real-World Visualization Interface for Public EngagementSébastien Lallé, Cristina Conati, Giuseppe Carenini. 369-370 [doi]
- Are Item Attributes a Good Alternative to Context Elicitation in Recommender Systems?Amaury L'Huillier, Sylvain Castagnos, Anne Boyer. 371-372 [doi]
- Item Contents Good, User Tags Better: Empirical Evaluation of a Food Recommender SystemDavid Massimo, Mehdi Elahi, Mouzhi Ge, Francesco Ricci. 373-374 [doi]
- A Hybrid Recommendation Framework Exploiting Linked Open Data and Graph-based FeaturesCataldo Musto, Giovanni Semeraro, Marco de Gemmis, Pasquale Lops. 375-376 [doi]
- Combining Long-term and Discussion-generated Preferences in Group RecommendationsThuy Ngoc Nguyen, Francesco Ricci. 377-378 [doi]
- Evaluation of Learners' Adjustment of Question Difficulty in Adaptive Practice of FactsJan Papousek, Radek Pelánek. 379-380 [doi]
- An Evaluation of Learning-to-Rank Methods for Lurking Behavior AnalysisDiego Perna, Andrea Tagarelli. 381-382 [doi]
- Learning Inclination to Empathy from Social Media FootprintsMarco Polignano, Pierpaolo Basile, Gaetano Rossiello, Marco de Gemmis, Giovanni Semeraro. 383-384 [doi]
- Using System Dynamics to Model Student Performance in an Intelligent Tutoring SystemMaría T. Sanz, David Arnau, José Antonio González-Calero, Miguel Arevalillo-Herráez. 385-386 [doi]
- Measuring Bias in News Websites, Towards a Model for PersonalizationBrendan Spillane, Séamus Lawless, Vincent Wade. 387-388 [doi]
- A Unified Latent Factor Model for Effective Category-Aware RecommendationZhu Sun, Guibing Guo, Jie Zhang, Chi Xu. 389-390 [doi]
- Sequences of Diverse Song Recommendations: An Exploratory Study in a Commercial SystemNava Tintarev, Christoph Lofi, Cynthia C. S. Liem. 391-392 [doi]
- A Personalized Global Filter To Predict RetweetsMichail Vougioukas, Ion Androutsopoulos, Georgios Paliouras. 393-394 [doi]
- User Expertise Inference on Twitter: Learning from Multiple Types of User DataYu Xu, Dong Zhou, Séamus Lawless. 395-396 [doi]
- A Neural Time Series Forecasting Model for User Interests Prediction On TwitterLemei Zhang, Peng Liu, Jon Atle Gulla. 397-398 [doi]
- Indirect Context SuggestionYong Zheng. 399-400 [doi]