ABSTRACT
Recent advancements in artificial intelligence (AI) create new opportunities for implementing a wide range of intelligent user interfaces. Speech-based interfaces, chatbots, visual recognition of users and objects, recommender systems, and adaptive user interfaces are examples that have majored over the last 10 years due to new approaches in machine learning (ML). Modern ML-techniques outperform in many domains of previous approaches and enable new applications. Today, it is possible to run models efficiently on various devices, including PCs, smartphones, and embedded systems. Leveraging the potential of artificial intelligence and combining them with human-computer interaction approaches allows developing intelligent user interfaces supporting users better than ever before. This course introduces participants to terms and concepts relevant in AI and ML. Using examples and application scenarios, we practically show how intelligent user interfaces can be designed and implemented. In particular, we look at how to create optimized keyboards, use natural language processing for text and speech-based interaction, and how to implement a recommender system for movies. Thus, this course aims to introduce participants to a set of machine learning tools that will enable them to build their own intelligent user interfaces. This course will include video based lectures to introduce concepts and algorithms supported by practical and interactive exercises using python notebooks.
- Daniel Buschek and Florian Alt. 2017. ProbUI: Generalising Touch Target Representations to Enable Declarative Gesture Definition for Probabilistic GUIs. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Denver, CO, USA) (CHI ’17). New York, NY, USA. https://doi.org/10.1145/3025453.3025502Google ScholarDigital Library
- Daniel Buschek, Julia Kinshofer, and Florian Alt. 2018. A Comparative Evaluation of Spatial Targeting Behaviour Patterns for Finger and Stylus Tapping on Mobile Touchscreen Devices. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 1, 4, Article 126 (Jan. 2018), 21 pages. https://doi.org/10.1145/3161160Google ScholarDigital Library
- Daniel Buschek, Martin Zürn, and Malin Eiband. 2021. The Impact of Multiple Parallel Phrase Suggestions on Email Input and Composition Behaviour of Native and Non-Native English Writers. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (Yokohama, JP) (CHI ’21). ACM, New York, NY, USA.Google ScholarDigital Library
- Huy Viet Le, Sven Mayer, and Niels Henze. 2021. Deep Learning for Human-Computer Interaction. Interactions (2021). https://doi.org/10.1145/3436958Google ScholarDigital Library
- Huy Viet Le, Sven Mayer, Maximilian Weiß, Jonas Vogelsang, Henrike Weingärtner, and Niels Henze. 2020. Shortcut Gestures for Mobile Text Editing on Fully Touch Sensitive Smartphones. ACM Trans. Comput.-Hum. Interact. 27, 5, Article 33 (Aug. 2020), 38 pages. https://doi.org/10.1145/3396233Google ScholarDigital Library
- A. Oulasvirta, N. R. Dayama, M. Shiripour, M. John, and A. Karrenbauer. 2020. Combinatorial Optimization of Graphical User Interface Designs. Proc. IEEE 108, 3 (March 2020), 434–464. https://doi.org/10.1109/JPROC.2020.2969687 Conference Name: Proceedings of the IEEE.Google ScholarCross Ref
- Antti Oulasvirta, Per Ola Kristensson, Xiaojun Bi, and Andrew Howes (Eds.). 2018. Computational Interaction. Oxford University Press.Google Scholar
- Albrecht Schmidt. 2020. Interactive Human Centered Artificial Intelligence: A Definition and Research Challenges. In Proceedings of the International Conference on Advanced Visual Interfaces (Salerno, Italy) (AVI ’20). Association for Computing Machinery, New York, NY, USA, Article 3, 4 pages. https://doi.org/10.1145/3399715.3400873Google ScholarDigital Library
- Albrecht Schmidt and Thomas Herrmann. 2017. Intervention User Interfaces: A New Interaction Paradigm for Automated Systems. Interactions 24, 5 (Aug. 2017), 40–45. https://doi.org/10.1145/3121357Google ScholarDigital Library
Index Terms
- Introduction to Intelligent User Interfaces
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