Wu / Li | Knowledge Management and Acquisition for Intelligent Systems | Buch | 978-981-9281-52-7 | www.sack.de

Buch, Englisch, 184 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Computer Science

Wu / Li

Knowledge Management and Acquisition for Intelligent Systems

22nd Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2026, Guangzhou, China, November 17–18, 2026, Proceedings
Erscheinungsjahr 2027
ISBN: 978-981-9281-52-7
Verlag: Springer

22nd Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2026, Guangzhou, China, November 17–18, 2026, Proceedings

Buch, Englisch, 184 Seiten, Format (B × H): 155 mm x 235 mm

Reihe: Lecture Notes in Computer Science

ISBN: 978-981-9281-52-7
Verlag: Springer


This book constitutes the refereed proceedings of the 22nd Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2026, held in Guangzhou, China, during November 17-18, 2026.

The 8 full papers and 5 short papers included in this book were carefully reviewed and selected from 30 submissions. This volume PKAW has provided a forum for researchers to exchange ideas and discuss advances in knowledge acquisition, a fundamental area of Artificial Intelligence (AI). Its scope has evolved beyond traditional human-centered knowledge acquisition to encompass related areas such as knowledge engineering, knowledge management, machine learning, and data mining, reflecting the broader development of AI research.

Wu / Li Knowledge Management and Acquisition for Intelligent Systems jetzt bestellen!

Zielgruppe


Research


Autoren/Hrsg.


Weitere Infos & Material


.- Brainwave-Informed Knowledge Acquisition for HR Development.
.- TMBM: A Temporal Multi-Behavior Model for Influence Propagation in Social Networks.
.- A Collaborative Large Language Model-Guided Evolutionary Framework for Fair Multiobjective Influence Maximisation.
.- From Tables to Graph: A Unified Framework for Knowledge Graph Construction from Complex Relational Databases.
.- FactRebuild: Zero-Resource Hallucination Detection via Weighted Fact Decomposition and Question Reverse Reconstruction.
.- CD-ViewGNN: Persistence-Anchored Forecasting of Cluster-Density Dynamics in Event-Centred Discussions.
.- RoleMem: Role-Specific Multilayer Memory for Question Answering Agents in Long-Term Conversations.
.- GeoKORE: Schema-Aware LLM-based Geological Knowledge Extraction for Reliable Knowledge Graph Construction.
.- Does Concept Drift Affect SHAP Explanation Stability in Credit Scoring? Formalising the Performance–Explanation Decoupling Paradox and a Composite Governance Metric.
.- Human Reason Logs as Knowledge Acquisition Data for Reason-Visible AI-Assisted Judgment.
.- Explainable Knowledge Discovery from Historical Post-Earthquake Road Recovery Data Using XGBoost and SHAP.
.- Structuring Tacit Coaching Knowledge for AI-Assisted Sprint Feedback.
.- Dynamic Feature Purification via Lee Oscillators for Fake News Detection: An Exploratory Cross-Architecture Study.



Ihre Fragen, Wünsche oder Anmerkungen
Vorname*
Nachname*
Ihre E-Mail-Adresse*
Kundennr.
Ihre Nachricht*
Lediglich mit * gekennzeichnete Felder sind Pflichtfelder.
Wenn Sie die im Kontaktformular eingegebenen Daten durch Klick auf den nachfolgenden Button übersenden, erklären Sie sich damit einverstanden, dass wir Ihr Angaben für die Beantwortung Ihrer Anfrage verwenden. Selbstverständlich werden Ihre Daten vertraulich behandelt und nicht an Dritte weitergegeben. Sie können der Verwendung Ihrer Daten jederzeit widersprechen. Das Datenhandling bei Sack Fachmedien erklären wir Ihnen in unserer Datenschutzerklärung.