ABIS 2019 - 23rd Intl. Workshop on Personalization and Recommendation on the Web and Beyond

Permanent URI for this collectionhttps://dl.gi.de/handle/20.500.12116/32303

ABIS 2019 is an international workshop, organized by the SIG on Adaptivity and User Modeling of the German Gesellschaft fur Informatik. For more than 20 years, the ABIS Workshop has been a highly interactive forum for discussing the state of the art in personalization and user modeling. Latest developments in industry and research are presented in plenary sessions, forums, and tutorials.

For the first time, ABIS will be hosted by the ACM International Conference on Hypertext and Social Media (HT'19), which will celebrate its 30th anniversary this year. ABIS 2019 additionally features the introduction of the new book on Personalized Human-Computer Interaction, edited by the workshop chairs and to be published in 2019 by DeGruyter.

Authors with most Documents  

Atzmueller, Martin
2
Shayan, Parisa
2
Abascal, Julio
1
Arbelaitz, Olatz
1
Dietz, Linus W.
1

Most Cited Items (h5index: 0, h5median: 0.0)

7
Unexpected and Unpredictable: Factors That Make Personalized Advertisements Creepy, Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond (2019)
4
Personalizing the User Interface for People with Disabilities, Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond (2019)
3
Towards Requirements for Intelligent Mentoring Systems, Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond (2019)
2
Modeling Physiological Conditions for Proactive Tourist Recommendations, Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond (2019)
17
Explanations and User Control in Recommender Systems, Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond (2019)
1
Behavioral Analysis on Socio-Spatial Interaction Networks concerning User Preferences, Interactions and their Perception, Proceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond (2019)

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Number of citations to items in this collection: 34 (from the 8 items 6 items have citations)

  • Eelco Herder, Stijn Dirks (2022): User Attitudes Towards Commercial Versus Political Microtargeting, In: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, doi:10.1145/3511047.3538027
  • Kristina Radivojevic, Nicholas Clark, Anna Klempay, Paul Brenner (2024): Defending novice user privacy: An evaluation of default web browser configurations, In: Computers & Security, doi:10.1016/j.cose.2024.103784
  • Eelco Herder, Daniel Roßner, Claus Atzenbeck (2020): Reflecting on Social Media Behavior by Structuring and Exploring Posts and Comments, In: i-com 3(19), doi:10.1515/icom-2020-0019
  • Eelco Herder, Olaf van Maaren (2020): Privacy Dashboards: The Impact of the Type of Personal Data and User Control on Trust and Perceived Risk, In: Adjunct Publication of the 28th ACM Conference on User Modeling, Adaptation and Personalization, doi:10.1145/3386392.3399557
  • Maral Abdollahi, Yuming Fang, Hanjie Liu, Claire M. Segijn (2023): Examining Affect, Relevance, and Creepiness as Underlying Mechanisms of Consumers’ Attitudes Toward Synced Ads in Valenced Contexts, In: European Advertising Academy, doi:10.1007/978-3-658-40429-1_5
  • Arti Sharma, Abhishek Vashishta, Achin Shahi, Ashwin Saxena, Harshil Kumar Gulati (2022): Study of Video Suggestions based on Calendar Events, In: 2022 6th International Conference on Intelligent Computing and Control Systems (ICICCS), doi:10.1109/iciccs53718.2022.9788466
  • Yim Register, Lucy Qin, Amanda Baughan, Emma S. Spiro (2023): Attached to “The Algorithm”: Making Sense of Algorithmic Precarity on Instagram, In: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, doi:10.1145/3544548.3581257
  • Luz Santamaria-Granados, Juan Francisco Mendoza-Moreno, Gustavo Ramirez-Gonzalez (2020): Tourist Recommender Systems Based on Emotion Recognition—A Scientometric Review, In: Future Internet 1(13), doi:10.3390/fi13010002
  • Kristian Dokic, Domagoj Sulc, Dubravka Mandusic (2021): Collecting Big Data in Cinemas to Improve Recommendation Systems - A Model with Three Types of Motion Sensors, In: Lecture Notes in Business Information Processing, doi:10.1007/978-3-030-92909-1_17
  • Nazish Nouman, Zubair Ahmed Shaikh, Shaukat Wasi (2024): A Novel Personalized Learning Framework With Interactive e-Mentoring, In: IEEE Access, doi:10.1109/access.2024.3354167
  • Ralf Klamma, Peter de Lange, Alexander Tobias Neumann, Benedikt Hensen, Milos Kravcik, Xia Wang, Jakub Kuzilek (2020): Scaling Mentoring Support with Distributed Artificial Intelligence, In: Lecture Notes in Computer Science, doi:10.1007/978-3-030-49663-0_6
  • Laura Schelenz (2022): Diversity Concepts in Computer Science and Technology Development: A Critique, In: Science, Technology, & Human Values 5(48), doi:10.1177/01622439221122549
  • Diego Addan Gonçalves, Maria Cecilia Calani Baranauskas, Julio Cesar dos Reis (2020): Accessibility in Pervasive Systems: An Exploratory Study, In: Lecture Notes in Computer Science, doi:10.1007/978-3-030-50344-4_3
  • Diego Addan Gonçalves, Ricardo Edgard Caceffo, Maria Cecilia Calani Baranauskas (2021): Analysis of Emotion in Socioenactive Systems, In: Lecture Notes in Computer Science, doi:10.1007/978-3-030-78462-1_41
  • Laura Schelenz (2022): Diversity Concepts in Computer Science and Technology Development: A Critique, In: Science, Technology, & Human Values 5(48), doi:10.1177/01622439221122549
  • Adele Smolansky, Miranda Yang, Shiri Azenkot (2024): Towards Designing Digital Learning Tools for Students with Cortical/Cerebral Visual Impairments: Leveraging Insights from Teachers of the Visually Impaired, In: The 26th International ACM SIGACCESS Conference on Computers and Accessibility, doi:10.1145/3663548.3675636
  • Martin Atzmueller, Cicek Guven, Parisa Shayan, Spyroula Masiala, Rick Mackenbach, Werner Liebregts (2019): Observing and Modeling User Behavior on Socio-Spatial Interaction Networks: Conformance, Exceptions, and Anomalies, In: 2019 First International Conference on ​Transdisciplinary AI (TransAI), doi:10.1109/transai46475.2019.00013
  • Mengke Wu, Weizi Liu, Yanyun Wang, Mike Yao (2025): Negotiating the Shared Agency between Humans & AI in the Recommender System, In: Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems, doi:10.1145/3706599.3719900
  • Ibrahim Al-Hazwani, Tiantian Luo, Oana Inel, Francesco Ricci, Mennatallah El-Assady, Jürgen Bernard (2024): ScrollyPOI: A Narrative-Driven Interactive Recommender System for Points-of-Interest Exploration and Explainability, In: Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization, doi:10.1145/3631700.3665183
  • Zhongli Filippo Hu, Noemi Mauro, Giovanna Petrone, Liliana Ardissono (2023): Service-based Presentation of Multimodal Information for the Justification of Recommender Systems Results, In: Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, doi:10.1145/3565472.3592962
  • Sachita Nishal, Jasmine Sinchai, Nicholas Diakopoulos (2024): Understanding Practices around Computational News Discovery Tools in the Domain of Science Journalism, In: Proceedings of the ACM on Human-Computer Interaction CSCW1(8), doi:10.1145/3637419
  • Thi Ngoc Trang Tran, Alexander Felfernig, Viet Man Le, Thi Minh Ngoc Chau, Thu Giang Mai (2023): User Needs for Explanations of Recommendations: In-depth Analyses of the Role of Item Domain and Personal Characteristics, In: Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, doi:10.1145/3565472.3592950
  • Ester Bartels, Aletta Smits, Chris Detweiler, Esther van der Stappen, Suzanne van Rossen, Shakila Shayan, Katja Pott, Karine Cardona, Jürgen Ziegler, Koen van Turnhout (2024): Exploring Categorizations of Algorithmic Affordances in Graphical User Interfaces of Recommender Systems, In: Lecture Notes in Computer Science, doi:10.1007/978-3-031-61698-3_16
  • Alberto Carlo Maria Mancino, Antonio Ferrara, Salvatore Bufi, Daniele Malitesta, Tommaso Di Noia, Eugenio Di Sciascio (2023): KGTORe: Tailored Recommendations through Knowledge-aware GNN Models, In: Proceedings of the 17th ACM Conference on Recommender Systems, doi:10.1145/3604915.3608804
  • Noemi Mauro, Zhongli Filippo Hu, Liliana Ardissono (2022): Justification of recommender systems results: a service-based approach, In: User Modeling and User-Adapted Interaction 3(33), doi:10.1007/s11257-022-09345-8
  • Mouadh Guesmi, Mohamed Amine Chatti, Shoeb Joarder, Qurat Ul Ain, Clara Siepmann, Hoda Ghanbarzadeh, Rawaa Alatrash (2023): Justification vs. Transparency: Why and How Visual Explanations in a Scientific Literature Recommender System, In: Information 7(14), doi:10.3390/info14070401
  • Mouadh Guesmi, Mohamed Amine Chatti, Shoeb Joarder, Qurat Ul Ain, Rawaa Alatrash, Clara Siepmann, Tannaz Vahidi (2023): Interactive Explanation with Varying Level of Details in an Explainable Scientific Literature Recommender System, In: International Journal of Human–Computer Interaction 22(40), doi:10.1080/10447318.2023.2262797
  • Jeonguk Hong, Gyewon Jeon, Sangyeon Kim, Sangwon Lee (2025): Find Your Social Match, Discover What to Watch: The Role of Social Profiles and Explanations in Recommender Systems, In: International Journal of Human–Computer Interaction 8(42), doi:10.1080/10447318.2025.2546662
  • Lemei Zhang, Peng Liu, Jon Atle Gulla (2023): Recommending on graphs: a comprehensive review from a data perspective, In: User Modeling and User-Adapted Interaction 4(33), doi:10.1007/s11257-023-09359-w
  • Corinna Breitinger, Birkan Kolcu, Monique Meuschke, Norman Meuschke, Bela Gipp (2020): Supporting the Exploration of Semantic Features in Academic Literature using Graph-based Visualizations, In: Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020, doi:10.1145/3383583.3398599
  • Mohamed Amine Chatti, Mouadh Guesmi, Arham Muslim (2024): Visualization for Recommendation Explainability: A Survey and New Perspectives, In: ACM Transactions on Interactive Intelligent Systems 3(14), doi:10.1145/3672276
  • Yingqiang Ge, Shuchang Liu, Zuohui Fu, Juntao Tan, Zelong Li, Shuyuan Xu, Yunqi Li, Yikun Xian, Yongfeng Zhang (2024): A Survey on Trustworthy Recommender Systems, In: ACM Transactions on Recommender Systems 2(3), doi:10.1145/3652891
  • Shagun Jhaver, Alice Qian Zhang, Quan Ze Chen, Nikhila Natarajan, Ruotong Wang, Amy X. Zhang (2023): Personalizing Content Moderation on Social Media: User Perspectives on Moderation Choices, Interface Design, and Labor, In: Proceedings of the ACM on Human-Computer Interaction CSCW2(7), doi:10.1145/3610080
  • Lamia Zouhaier, Yousra Ben Daly Hlaoui, Leila Ben Ayed (2021): A Reinforcement Learning Based Approach of Context-driven Adaptive User Interfaces, In: 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC), doi:10.1109/compsac51774.2021.00217
Please note: Providing information about citations is only possible thanks to to the open metadata APIs provided by crossref.org and opencitations.net. These lists may be incomplete due to unavailable citation data.source: opencitations.net, crossref.org