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ORCID25. UMAP 2017: Bratislava, Slovakia
- Mária Bieliková, Eelco Herder, Federica Cena, Michel C. Desmarais:
Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, UMAP 2017, Bratislava, Slovakia, July 09 - 12, 2017. ACM 2017, ISBN 978-1-4503-4635-1
Keynote Addresses
- Paul De Bra:
After Twenty-Five Years of User Modeling and Adaptation...What Makes us UMAP? 1 - Jennifer Golbeck:
I'll be Watching You: Policing the Line between Personalization and Privacy. 2 - Pearl Pu:
Emotion Analysis in Natural Language. 3
Long Papers
- Sarah Bashirieh, Sepideh Mesbah, Judith Redi, Alessandro Bozzon
, Zoltán Szlávik, Robert-Jan Sips:
Nudge your Workforce: A Study on the Effectiveness of Task Notification Strategies in Enterprise Mobile Crowdsourcing. 4-12 - Robin Devooght, Hugues Bersini:
Long and Short-Term Recommendations with Recurrent Neural Networks. 13-21 - Vania Dimitrova, Antonija Mitrovic, Alicja Piotrkowicz, Lydia Lau, Amali Weerasinghe:
Using Learning Analytics to Devise Interactive Personalised Nudges for Active Video Watching. 22-31 - Crícia Z. Felício, Klérisson V. R. Paixão, Célia A. Zorzo Barcelos, Philippe Preux:
A Multi-Armed Bandit Model Selection for Cold-Start User Recommendation. 32-40 - Julio Daniel Guerra Hollstein, Jordan Barria-Pineda, Christian D. Schunn, Susan Bull, Peter Brusilovsky:
Fine-Grained Open Learner Models: Complexity Versus Support. 41-49 - Seyyed Hadi Hashemi, Jaap Kamps:
Where To Go Next?: Exploiting Behavioral User Models in Smart Environments. 50-58 - Charif Haydar, Anne Boyer:
A New Statistical Density Clustering Algorithm based on Mutual Vote and Subjective Logic Applied to Recommender Systems. 59-66 - Daniel Herzog, Hesham Massoud, Wolfgang Wörndl:
RouteMe: A Mobile Recommender System for Personalized, Multi-Modal Route Planning. 67-75 - Roya Hosseini, Peter Brusilovsky, Michael Yudelson, Arto Hellas:
Stereotype Modeling for Problem-Solving Performance Predictions in MOOCs and Traditional Courses. 76-84 - Yun Huang, Julio Daniel Guerra Hollstein, Jordan Barria-Pineda, Peter Brusilovsky:
Learner Modeling for Integration Skills. 85-93 - Stephen Hutt, Caitlin Mills, Nigel Bosch, Kristina Krasich, James R. Brockmole, Sidney K. D'Mello:
"Out of the Fr-Eye-ing Pan": Towards Gaze-Based Models of Attention during Learning with Technology in the Classroom. 94-103 - Kevin Jasberg, Sergej Sizov:
Probabilistic Perspectives on Collecting Human Uncertainty in Predictive Data Mining. 104-112 - Iman Kamehkhosh, Dietmar Jannach:
User Perception of Next-Track Music Recommendations. 113-121 - Shiri Kremer-Davidson, Inbal Ronen, Avi Kaplan, Maya Barnea:
"Personal Social Dashboard": A Tool for Measuring Your Social Engagement Effectiveness in the Enterprise. 122-130 - Vikas Kumar, Saeideh Bakhshi, Lyndon Kennedy, David A. Shamma:
Adaptive City Characteristics: How Location Familiarity Changes What Is Regionally Descriptive. 131-139 - Juliet Okpo, Judith Masthoff, Matt Dennis, Nigel A. Beacham, Ana Ciocarlan:
Investigating the Impact of Personality and Cognitive Efficiency on the Selection of Exercises for Learners. 140-147 - Zachary A. Pardos, Anant Dadu:
Imputing KCs with Representations of Problem Content and Context. 148-155 - Radek Pelánek, Jirí Rihák:
Experimental Analysis of Mastery Learning Criteria. 156-163 - George E. Raptis, Christina P. Katsini, Marios Belk, Christos Fidas, George Samaras, Nikolaos M. Avouris:
Using Eye Gaze Data and Visual Activities to Infer Human Cognitive Styles: Method and Feasibility Studies. 164-173 - Dimitris Sacharidis:
Group Recommendations by Learning Rating Behavior. 174-182 - Augusto Dias Pereira dos Santos, Kalina Yacef, Roberto Martínez Maldonado:
Let's Dance: How to Build a User Model for Dance Students Using Wearable Technology. 183-191 - Robert Sawyer, Andy Smith, Jonathan P. Rowe, Roger Azevedo, James C. Lester:
Enhancing Student Models in Game-based Learning with Facial Expression Recognition. 192-201 - Alessandro Suglia, Claudio Greco, Cataldo Musto, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro:
A Deep Architecture for Content-based Recommendations Exploiting Recurrent Neural Networks. 202-211 - Vasileios Triglianos, Sambit Praharaj, Cesare Pautasso, Alessandro Bozzon, Claudia Hauff:
Measuring Student Behaviour Dynamics in a Large Interactive Classroom Setting. 212-220 - Moshe Unger, Bracha Shapira, Lior Rokach, Ariel Bar:
Inferring Contextual Preferences Using Deep Auto-Encoding. 221-229 - Fatemeh Vahedian, Robin D. Burke, Bamshad Mobasher:
Weighted Random Walk Sampling for Multi-Relational Recommendation. 230-237 - Wen Wu, Li Chen, Qingchang Yang:
Inferring Students' Sense of Community from Their Communication Behavior in Online Courses. 238-246 - SooJeong Yoo, Tristan Heywood, Lie Ming Tang, Bob Kummerfeld, Judy Kay:
Towards a Long Term Model of Virtual Reality Exergame Exertion. 247-255 - Shi Zong, Branislav Kveton, Shlomo Berkovsky, Azin Ashkan, Zheng Wen:
Get to the Bottom: Causal Analysis for User Modeling. 256-264
Short Papers
- Homayun Afrabandpey, Tomi Peltola, Samuel Kaski:
Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction. 265-269 - Vito Walter Anelli, Vito Bellini, Tommaso Di Noia, Wanda La Bruna, Paolo Tomeo, Eugenio Di Sciascio:
An Analysis on Time- and Session-aware Diversification in Recommender Systems. 270-274 - Leonardo Cella, Stefano Cereda, Massimo Quadrana, Paolo Cremonesi:
Deriving Item Features Relevance from Past User Interactions. 275-279 - Farzad Eskandanian, Bamshad Mobasher, Robin Burke:
A Clustering Approach for Personalizing Diversity in Collaborative Recommender Systems. 280-284 - Bruce Ferwerda, Marko Tkalcic, Markus Schedl:
Personality Traits and Music Genres: What Do People Prefer to Listen To? 285-288 - Saikishore Kalloori, Francesco Ricci:
Improving Cold Start Recommendation by Mapping Feature-Based Preferences to Item Comparisons. 289-293 - Vikas Kumar, Saeideh Bakhshi, Lyndon Kennedy, David A. Shamma:
The Force Within: Recommendations Via Gravitational Attraction Between Items. 294-297 - Antoine Lefebvre-Brossard, Alexandre Spaeth, Michel C. Desmarais:
Encoding User as More Than the Sum of Their Parts: Recurrent Neural Networks and Word Embedding for People-to-people Recommendation. 298-302 - Ryan Lowe, Ben Steichen:
Multilingual Search User Behaviors - Exploring Multilingual Querying and Result Selection Through Crowdsourcing. 303-307 - Roberto Martínez Maldonado, Mykola Pechenizkiy, Simon Buckingham Shum, Tamara Power, Carolyn Hayes, Carmen Axisa:
Modelling Embodied Mobility Teamwork Strategies in a Simulation-Based Healthcare Classroom. 308-312 - Chun-Hua Tsai, Peter Brusilovsky:
Providing Control and Transparency in a Social Recommender System for Academic Conferences. 313-317
Doctoral Consortium Papers
- Ifeoma Adaji:
Towards Improving E-commerce Users Experience Using Personalization & Persuasive Technology. 318-321 - Carine Pierrette Mukamakuza:
Analyzing the Impact of Social Connections on Rating Behavior in Social Recommender Systems. 322-326 - Hebatallah A. Mohamed Hassan:
Personalized Research Paper Recommendation using Deep Learning. 327-330 - Thuy Ngoc Nguyen:
Conversational Group Recommender Systems. 331-334 - Augusto Dias Pereira dos Santos:
Smart Technology for Supporting Dance Education. 335-338 - SooJeong Yoo:
Harnessing Virtual Reality Exergames and Physical Fitness Sensing to Create a Personalised Game and Dashboard. 339-342 - Mengdie Zhuang:
Modelling User Behaviour based on Process. 343-346
Extended Abstracts
- Himan Abdollahpouri, Robin Burke, Bamshad Mobasher:
Recommender Systems as Multistakeholder Environments. 347-348 - Ifeoma Adaji, Julita Vassileva:
Towards Understanding Users' Motivation in a Q&A Social Network Using Social Influence and the Moderation by Culture. 349-350 - Saeed Amal, Tsvi Kuflik, Einat Minkov:
Harvesting Entity-relation Social Networks from the Web: Potential and Challenges. 351-352 - Liliana Ardissono, Maurizio Ferrero, Giovanna Petrone, Marino Segnan:
Enhancing Collaborative Filtering with Friendship Information. 353-354 - Miguel Arevalillo-Herráez, Aladdin Ayesh, Olga C. Santos, Pablo Arnau-González:
Combining Supervised and Unsupervised Learning to Discover Emotional Classes. 355-356 - Francesco Barile, Judith Masthoff, Silvia Rossi:
The Adaptation of an Individual's Satisfaction to Group Context: the Role of Ties Strength and Conflicts. 357-358 - Hao Cheng, Markus Rokicki, Eelco Herder:
The Influence of City Size on Dietary Choices and Food Recommendation. 359-360 - Tomas Chovanak, Ondrej Kassák, Mária Bieliková:
Behavioral Patterns Mining for Online Time Personalization. 361-362 - Elena Viorica Epure, Benjamin Kille, Jon Espen Ingvaldsen, Rébecca Deneckère, Camille Salinesi, Sahin Albayrak:
Modeling the Dynamics of Online News Reading Interests. 363-364 - Liron Ben Kimon, Yisroel Mirsky, Lior Rokach, Bracha Shapira:
User Verification on Mobile Devices Using Sequences of Touch Gestures. 365-366 - Bob Kummerfeld, Judy Kay:
User Modeling for the Internet of Things. 367-368 - Sébastien Lallé, Cristina Conati, Giuseppe Carenini:
Impact of Individual Differences on User Experience with a Real-World Visualization Interface for Public Engagement. 369-370 - Amaury L'Huillier, Sylvain Castagnos, Anne Boyer:
Are Item Attributes a Good Alternative to Context Elicitation in Recommender Systems? 371-372 - David Massimo, Mehdi Elahi, Mouzhi Ge, Francesco Ricci:
Item Contents Good, User Tags Better: Empirical Evaluation of a Food Recommender System. 373-374 - Cataldo Musto, Giovanni Semeraro, Marco de Gemmis, Pasquale Lops:
A Hybrid Recommendation Framework Exploiting Linked Open Data and Graph-based Features. 375-376 - Thuy Ngoc Nguyen, Francesco Ricci:
Combining Long-term and Discussion-generated Preferences in Group Recommendations. 377-378 - Jan Papousek, Radek Pelánek:
Evaluation of Learners' Adjustment of Question Difficulty in Adaptive Practice of Facts. 379-380 - Diego Perna, Andrea Tagarelli:
An Evaluation of Learning-to-Rank Methods for Lurking Behavior Analysis. 381-382 - Marco Polignano, Pierpaolo Basile, Gaetano Rossiello, Marco de Gemmis, Giovanni Semeraro:
Learning Inclination to Empathy from Social Media Footprints. 383-384 - María T. Sanz, David Arnau, José Antonio González-Calero, Miguel Arevalillo-Herráez:
Using System Dynamics to Model Student Performance in an Intelligent Tutoring System. 385-386 - Brendan Spillane, Séamus Lawless, Vincent Wade:
Measuring Bias in News Websites, Towards a Model for Personalization. 387-388 - Zhu Sun, Guibing Guo, Jie Zhang, Chi Xu:
A Unified Latent Factor Model for Effective Category-Aware Recommendation. 389-390 - Nava Tintarev, Christoph Lofi, Cynthia C. S. Liem:
Sequences of Diverse Song Recommendations: An Exploratory Study in a Commercial System. 391-392 - Michail Vougioukas, Ion Androutsopoulos, Georgios Paliouras:
A Personalized Global Filter To Predict Retweets. 393-394 - Yu Xu, Dong Zhou, Séamus Lawless:
User Expertise Inference on Twitter: Learning from Multiple Types of User Data. 395-396 - Lemei Zhang, Peng Liu, Jon Atle Gulla:
A Neural Time Series Forecasting Model for User Interests Prediction On Twitter. 397-398 - Yong Zheng:
Indirect Context Suggestion. 399-400
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