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Cognitive Computing - ICCC 2024: 8th International Conference, Held as Part of the Services Conference Federation, SCF 2024, Bangkok, Thailand, November 1619, 2024, Proceedings [Pehme köide]

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  • Formaat: Paperback / softback, 129 pages, kõrgus x laius: 235x155 mm, 22 Illustrations, color; 6 Illustrations, black and white; XIII, 129 p. 28 illus., 22 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 15426
  • Ilmumisaeg: 30-Nov-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031779533
  • ISBN-13: 9783031779534
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  • Formaat: Paperback / softback, 129 pages, kõrgus x laius: 235x155 mm, 22 Illustrations, color; 6 Illustrations, black and white; XIII, 129 p. 28 illus., 22 illus. in color., 1 Paperback / softback
  • Sari: Lecture Notes in Computer Science 15426
  • Ilmumisaeg: 30-Nov-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031779533
  • ISBN-13: 9783031779534
This book constitutes the refereed proceedings of the 8th International Conference on Cognitive Computing, ICCC 2024, Held as Part of the Services Conference Federation, SCF 2024, held in Bangkok, Thailand, during November 1619, 2024.





The 6 full papers and 2 short papers included in this book were carefully reviewed and selected from 10 submissions. They were organized in topical sections as follows: research track; application track; and short paper track.
.- Research Track.



.- A Review of Link Prediction on Heterogeneous Networks.



.- Research on Firefly Algorithm Enhancement by Diversifying Swarm.



.- A Survey on Anomaly Detection With Few-Shot Learning.



.- Electromyography-Based Intentional-Deception Behavior Analysis in an
Interactive Social Context: Statistical Analysis and Machine Learning.



.- Application Track.



.- An Adaptive Hot Ranking Algorithm for Popular Item Recommendation in the
Express Industry.



.- Retrieval-Augmented Generation Architecture Framework: Harnessing the
Power of RAG.



.- Short Paper Track.



.- Application and Optimization of Multi-Agent Reinforcement Learning in
Collaborative Decision-Making.



.- LLM-Based Automating Product Information Retrieval for Industry Analysis:
A Real-World Application.