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Introduction to Intelligent User Interfaces

Title data

Schmidt, Albrecht ; Mayer, Sven ; Buschek, Daniel:
Introduction to Intelligent User Interfaces.
In: Kitamura, Yoshifumi ; Quigley, Aaron ; Isbister, Katherine ; Igarashi, Takeo (ed.): CHI EA '21 : Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. - New York : Association for Computing Machinery , 2021 . - No. 129
ISBN 978-1-4503-8095-9
DOI: https://doi.org/10.1145/3411763.3445021

Official URL: Volltext

Project information

Project title:
Project's official titleProject's id
AI Tools - Continuous Interaction with Computational Intelligence ToolsNo information

Abstract in another language

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.

Further data

Item Type: Article in a book
Refereed: No
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science VIII
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 31 May 2021 10:29
Last Modified: 31 May 2021 10:29
URI: https://eref.uni-bayreuth.de/id/eprint/65527