Connectionists: Call for Papers: 2020 Principle and Practice of Data and Knowledge Acquisition Workshop (PKAW2020)
Tran Son
sontn.fz at gmail.com
Sun Apr 19 01:17:12 EDT 2020
Call for Papers: 2020 Principle and Practice of Data and Knowledge Acquisition Workshop (PKAW2020), 11-12 July 2020, Yokohama, Japan
PKAW2020 is a workshop under IJCAI/PRICAI2020
PKAW (Principle and Practice of Data and Knowledge Acquisition Workshop) was established in 1980s as an integral part of PRICAI (Pacific Rim International Conference on Artificial Intelligence). PKAW2020 will be held as a workshop of the joint conference IJCAI/PRICAI2020 at Yokohama, Japan. Wide range of multidisciplinary topics concerning knowledge acquisition from data and/or human experts together with data acquisition, data representation etc. are greatly welcome.
IMPORTANT DATES:
- Submission Due: April 25, 2020 (Final paper submission will close at 11:59 PM GMT)
- Notification: May 25, 2020
- Camera Ready Due: June 5, 2020
- Workshop Date: July, 2020
TOPICS OF INTEREST
All aspects of knowledge acquisition, data engineering and management for intelligent systems, including (but not restricted to):
- Fundamental views on knowledge that affect the knowledge acquisition process and the use of knowledge in knowledge engineering
- Algorithmic approaches to knowledge acquisition
- Tools and techniques for knowledge acquisition, knowledge maintenance and knowledge validation
- Evaluation of knowledge acquisition techniques, tools and methods
- Languages and frameworks for knowledge and knowledge modelling information systems or decision support systems
- Methods and techniques for sharing and reusing knowledge
- Ontology and its role in knowledge acquisition
- Mining the Semantic Web, the Linked Data and the Web of Data
- Hybrid approaches combining knowledge engineering and machine learning
- Innovative user interfaces
- Data acquisition
- Data analytics and mining
- Multimedia data acquisition and analysis
- Data representation
- Big data acquisition and analysis
- Learning from big data
- Crowd-sourcing for data generation and problem solving
- Software engineering and knowledge engineering
- Algorithms, tools and techniques for machine intelligence
- Knowledge acquisition applications tested and deployed in in real-life settings
PAPER SUBMISSION:
PKAW will not accept any paper that, at the time of submission, is under review for, has already been published in, or has already been accepted for publication in, a journal or another venue with formally published proceedings. If part of the work has been previously published, authors are strongly encouraged to cite and compare/contrast the new contributions with the parts that were already published before. The paper must substantially extend the previously published work.
All papers for the review should be submitted electronically using the conference management tool in PDF/DOC format and formatted using the Springer LNAI template or IJICAI template. The paper should be between 10 to 15 pages long. Camera ready for accepted papers should be submitted using only the Springer LNAI template. For Springer LNAI format templates, please see the Springer’s website:
http://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines
Page limit:
Full paper: 12-15 pages
Short paper: 8 pages
Submission will be through the Easychair conference management system:
https://easychair.org/conferences/?conf=pkaw2020
POST-PROCEEDINGS PUBLICATION:
The post-proceedings of PKAW2020 will be published in the LNAI series of Springer
ORGANIZING COMMITTEE:
Honorary Chairs:
• Prof. Paul Compton, University of New South Wales, Australia
• Prof. Hiroshi Motoda, Osaka University, Japan
Advisory Committee:
• Prof. Maria R Lee, Shih Chien University, Taiwan
• Prof. Kenichi Yoshida, University of Tsukuba, Japan
• Prof. Byeong-Ho Kang, University of Tasmania, Australia
• Prof. Deborah Richards, Macquarie University, Australia
Workshop Co-chairs:
• A/Prof. Quan Bai, University of Tasmania, Australia
• Prof. Hiroshi Uehara, Akita Prefectural University, Japan
Publicity Chairs:
• Dr. Soyeon Caren Han, University of Sydney, Australia
• Dr. Son Tran, University of Tasmania, Australia
• A/Prof. Weiwei Yuan, Nanjing University of Aeronautics and Astronautics, China
• Dr. Takayasu Yamaguchi, Senior Research Engineer, NTT DOCOMO, Inc., Japan
Webmaster:
• Mr. Shiqing Wu, University of Tasmania, Australia
CONTACT:
A/Prof. Quan Bai: quan.bai at utas.edu.au
Prof. Hiroshi Uehara: uehara at akita-pu.ac.jp
Dr. Takayasu Yamaguchi: yamasound at gmail.com
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