Conference Information

PKAW 2026: Principle and practice of data and Knowledge Acquisition Workshop

Please Login to view website of conference
Free account: view official websites, track deadlines, and get email reminders.
Submission Date:
2026-07-15
Notification Date:
2026-09-15
Conference Date:
2026-11-17
Location:
Guangzhou, China
Years:
Add to calendar: Outlook / Apple (.ics)
ICORE: C   Viewed: 8885   Tracked: 0   Attend: 0
Embed deadline badge
PKAW
Get this via API
Search and ranking lists need no credentials at all; full detail for this page needs a free API key. See the developer guide.

Conference Partner Index (CP-I)

54.6 / 100
Ranked #891 of 5,693 conferences · Top 16%

#73 of 742 in Artificial Intelligence & Machine Learning

Academic recognition (35%)
58
Submission selectivity (20%) No data - scored at the neutral baseline of 50 —
Editions held (20%)
73
Community attention (10%)
15
Public record completeness (15%)
55

Inputs used: Listed as ICORE C · Editions on record: 14 · Researchers who opened this page in the past 24 months: 6

Missing from the public record: Historical acceptance rates (+4.5) · Best-paper records (+2.3)
Organizers can add these from this page after claiming the conference; scores are recomputed nightly. How to raise this score

Confidence 80% - the share of the score backed by observed data rather than the neutral baseline. How this score is calculated · Browse the ranking · Algorithm version 1.1 · Computed 2026-10-06

Call For Papers

PKAW 2026 (Principle and practice of data and Knowledge Acquisition Workshop) is a ICORE C conference held in Guangzhou, China on 2026-11-17. The paper submission deadline is 2026-07-15. Acceptance notifications are sent on 2026-09-15.

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). PKAW 2026 will be held at the 23rd Pacific Rim International Conference on Artificial Intelligence (PRICAI 2026) in Guangzhou, China. A wide range of topics related to knowledge acquisition and representation are greatly welcome. Topics of Interest All aspects of AI, machine learning, knowledge acquisition, data engineering and management for intelligent systems, including (but not restricted to): Knowledge Acquisition 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. Ontology and its role in knowledge acquisition Knowledge acquisition applications tested and deployed in real-life settings Knowledge Representation and Discovering Knowledge representation learning Temporal knowledge graph Data linkage Data analytics and mining Big data acquisition and analysis Machine learning/deep learning Semantic Web, the Linked Data and the Web of Data Responsible Data/Knowledge Management and System Transparency, explainability, trust, and accountability Privacy and security Other ethical concerns Knowledge-aware Application Question answering Recommendation system Domain-related application Human-centric Knowledge Engineering Human-machine collaboration, integration, interaction, delegation, dialog Hybrid approaches combining knowledge engineering and machine learning Other Topics Experience and Lesson learned Reproducibility and negative results of knowledge engineering Innovative user interfaces Crowd-sourcing for data generation and problem solving
Last updated by Admin Agent on

Related Conferences

Related Journals

CCFFull NameImpact FactorPublisherISSN
Control Engineering Practice5.3Elsevier0967-0661
AIEEE Transactions on Multimedia9.7IEEE1520-9210
CKnowledge-Based Systems7.2Elsevier0950-7051
BSoftware & Systems Modeling3.2Springer1619-1366
AIEEE Transactions on Computers3.8IEEE0018-9340
CFuture Generation Computer Systems5.9Elsevier0167-739X
CNeurocomputing6.5Elsevier0925-2312
CPattern Recognition Letters3.9Elsevier0167-8655
BPattern Recognition7.6Elsevier0031-3203
IEEE Access3.6IEEE2169-3536

Comments 0

No comments yet.

Please Login to post a comment