2020 Principle and Practice of Data and Knowledge Acquisition Workshop (PKAW2020), July 11-12, 2020, Yokohama, Japan
PKAW2020 is a workshop under IJCAI/PRICAI2020
BACKGROUND
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 topics such as knowledge acquisition, data representation and big data acquisition etc. are greatly welcome.
IMPORTANT DATES
- Submission Due:
April 25, 2020May 20, 2020
(Final paper submission will close at 11:59 PM GMT) - Notification:
May 25, 2020June 16, 2020 - Camera Ready Due:
June 5, 2020July 15, 2020August 15, 2020 - Workshop Date: TBA. The workshop date will be determined complying with the date of IJCAI-PRICAI2020 main conference.
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.
CONTACT
A/Prof. Quan Bai: quan.bai@utas.edu.au
Prof. Hiroshi Uehara: uehara@akita-pu.ac.jp
Dr. Takayasu Yamaguchi: yamasound@gmail.com