Welcome to the 2020 Principle and practice of data and Knowledge Acquisition Workshop (PKAW) to be held at Yokohama, Japan in July, 2020. Over the past two decades, PKAW has provided a forum for researchers and practitioners working in the area of knowledge acquisition and machine intelligence (MI, also Artificial Intelligence, AI).
PKAW 2020 will be collocated with the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI 2020). The purpose of this workshop is to provide a chance for intensive discussion on the aspects of knowledge acquisition and AI.
In recent years, unprecedented data, called big data, has become available and knowledge acquisition and learning from big data is increasing in importance. Various knowledge can be acquired not only from human experts but also from diverse data. Simultaneous acquisition from both data and human experts increases its importance. Multidisciplinary research including knowledge engineering, machine learning, natural language processing, human computer interaction, and artificial intelligence are required. We invite authors to submit papers on all aspects of these area.
Especially, according to the Gartner Hype Cycle for Emerging Technologies 2017, AI is one of the top emerging technology mega-trends. Artificial intelligence is changing the way in which organizations innovate and communicate their processes, products and services. Also in our daily life, AI embedded devices such as the smart speaker is about to become widely used, which extends the possibility of acquiring knowledge from users’ behavior observed through the interaction between those devices and their users.
Another important and related area is applications. Not only in the engineering field but also in the social science field (e.g., economics, social networks, and sociology), recent progress of knowledge acquisition and data engineering techniques is realizing interesting applications. We also invite submissions that present applications tested and deployed in real-life settings. Those papers should address lessons learned from application development and deployment.
All papers will be peer reviewed, and those accepted for the workshop will be included in the Springer LNAI proceedings.