Introduction to Intelligent User Interfaces

被引:1
作者
Schmidt, Albrecht [1 ]
Mayer, Sven [1 ]
Buschek, Daniel [2 ]
机构
[1] Ludwig Maximilians Univ Munchen, Munich, Germany
[2] Univ Bayreuth, Dept Comp Sci, Res Grp HCI AI, Bayreuth, Germany
来源
EXTENDED ABSTRACTS OF THE 2021 CHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'21) | 2021年
关键词
intelligent user interface; natural language interfaces; recommender systems; novel interaction techniques;
D O I
10.1145/3411763.3445021
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:4
相关论文
共 9 条
[1]   A Comparative Evaluation of Spatial Targeting Behaviour Patterns for Finger and Stylus Tapping on Mobile Touchscreen Devices [J].
Buschek, Daniel ;
Kinshofer, Julia ;
Alt, Florian .
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2017, 1 (04)
[2]   ProbUI: Generalising Touch Target Representations to Enable Declarative Gesture Definition for Probabilistic GUIs [J].
Buschek, Daniel ;
Alt, Florian .
PROCEEDINGS OF THE 2017 ACM SIGCHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'17), 2017, :4640-4653
[3]  
Buschek Daniel, 2021, P SIGCHI C HUM FACT
[4]  
Le H.V., 2020, Interactions, V28, P78, DOI DOI 10.1145/3436958
[5]   Shortcut Gestures for Mobile Text Editing on Fully Touch Sensitive Smartphones [J].
Le, Huy Viet ;
Mayer, Sven ;
Weiss, Maximilian ;
Vogelsang, Jonas ;
Weingaertner, Henrike ;
Henze, Niels .
ACM TRANSACTIONS ON COMPUTER-HUMAN INTERACTION, 2020, 27 (05)
[6]   Combinatorial Optimization of Graphical User Interface Designs [J].
Oulasvirta, Antti ;
Dayama, Niraj Ramesh ;
Shiripour, Morteza ;
John, Maximilian ;
Karrenbauer, Andreas .
PROCEEDINGS OF THE IEEE, 2020, 108 (03) :434-464
[7]  
Oulasvirta Antti, 2018, INTERACTION
[8]  
Schmidt A., 2017, INTERACTIONS, V24, P40, DOI [10.1145/3121357, DOI 10.1145/3121357]
[9]   Interactive Human Centered Artificial Intelligence: A Definition and Research Challenges [J].
Schmidt, Albrecht .
PROCEEDINGS OF THE WORKING CONFERENCE ON ADVANCED VISUAL INTERFACES AVI 2020, 2020,