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Knowledge and Systems Sciences: 23rd International Symposium, KSS 2024, Hobart, TAS, Australia, November 1617, 2024, Proceedings 2024 ed. [Mīkstie vāki]

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  • Formāts: Paperback / softback, 346 pages, height x width: 235x155 mm, 109 Illustrations, color; 28 Illustrations, black and white; XIX, 346 p. 137 illus., 109 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2269
  • Izdošanas datums: 17-Nov-2024
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819601770
  • ISBN-13: 9789819601776
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Knowledge and Systems Sciences: 23rd International Symposium, KSS 2024, Hobart, TAS, Australia, November 1617, 2024, Proceedings 2024 ed.Palielināt
  • Formāts: Paperback / softback, 346 pages, height x width: 235x155 mm, 109 Illustrations, color; 28 Illustrations, black and white; XIX, 346 p. 137 illus., 109 illus. in color., 1 Paperback / softback
  • Sērija : Communications in Computer and Information Science 2269
  • Izdošanas datums: 17-Nov-2024
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 9819601770
  • ISBN-13: 9789819601776
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9789819601776.html
Keywords:
This book constitutes the refereed proceedings of the 23rd International Symposium on Knowledge and Systems Sciences, KSS 2024, held in Hobart, Tasmania, Australia, during November 1617, 2024.





The 23 full papers presented in this book were carefully reviewed and selected from 50 submissions. They are organized in the following topical sections: Complex networks and modeling; Opinion dynamics; Knowledge technologies and systems engineering; Knowledge management.
.- Complex Networks and Modeling .



.- The Temporal Structural Pattern in Scientific Collaborative Behavior from
the Perspective of Complex Network.



.- The Analysis of Innovation Network in Chinas Hydrogen Energy Industry
from the Perspective of Patents.



.- Construction and Evaluation of a Subjects Synergistic Network for
Cross-regional Major Infectious Disease Emergency Response.



.- Evolution of cumulative reciprocity in structured populations.



.- Opinion Dynamics. 



.- Simulating Social Network Dynamics with LLM Agents: An Analysis of
Information Propagation and Echo Chambers.



.- How Public Opinion Risks in Social Hot Events Are Generated: A fsQCA
Perspective.



.- Vulnerability Measurement of Social Media Users to Online Public Opinion
in Emergency 

Context.



.- Analyzing Replies and Interactions among Users with Different Stances: A
Case Study of the Russia Ukraine Conflict.



.- Explainable Machine Learning-based Research on Key Factors in the
Formation of Public Opinion on Similar Events.



.- Knowledge Technologies and Systems Engineering.



.- UMCap: User Memory Augmented Method for Personalized Image Descriptions.



.- Research on the Construction Method of Island Chain Knowledge Graph.



.- A Knowledge and Data Driven Method for Air Combat Intention Recognition.



.- Model-Based Systems Engineering Supporting Architecture Modeling of Air
Traffic Management System and Model Verifying Based on SMT.



.- Mission Modeling for the Perseverance Rover based on KARMA Language.



.- Social Media oriented Fake News Detection based on Social Context and
Cascade Graph.



.- Data Augmentation Using Large Language Model for Fake Review
Identification.



.- Knowledge Management.



.- Digital Transformation Mechanisms for Emergency Management in Chemical
Enterprises: An  Industrial Agglomeration Perspective.



.- Research on the Credibility Evaluation Method of Online Medical Community
Answer Content 

Based on Domain Knowledge Graph.



.- A Comprehensive Framework for Sentiment Analysis and Cold-Start
Recommendations in 

Vietnam Hospitality Sector.



.- Mining Complementary Relationships of Items for Diversified
Recommendation.



.- A Novel Two-Stage Approach for Customer Satisfaction Analysis.



.- Predicting the decision-making performance based on self-attention and
long-short term memory network.



.- A Domain Knowledge-based Railway Equipment Fault Diagnosis Framework.