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Software Engineering and Management: Theory and Application: Volume 16 2024 ed. [Kõva köide]

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  • Formaat: Hardback, 238 pages, kõrgus x laius: 235x155 mm, 78 Illustrations, color; 25 Illustrations, black and white; VI, 238 p. 103 illus., 78 illus. in color., 1 Hardback
  • Sari: Studies in Computational Intelligence 1137
  • Ilmumisaeg: 03-May-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031551737
  • ISBN-13: 9783031551734
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Software Engineering and Management: Theory and Application: Volume 16 2024 ed.Suurem pilt
  • Formaat: Hardback, 238 pages, kõrgus x laius: 235x155 mm, 78 Illustrations, color; 25 Illustrations, black and white; VI, 238 p. 103 illus., 78 illus. in color., 1 Hardback
  • Sari: Studies in Computational Intelligence 1137
  • Ilmumisaeg: 03-May-2024
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3031551737
  • ISBN-13: 9783031551734
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783031551734.html
Märksõnad:
The book reports state of the art results in Software Engineering Research, Management & Applications in both printed and electronic form. SCI (Studies in Computation Intelligence) has grown into the most comprehensive computational intelligence research forum available in the world.





This volume published original papers on both theory and practice that address foundations, state of the art problems and solutions, and crucial challenges.
1. Changing Beauty Industrys Strategic: Focused on Metaverse and
Generation MZ.-
2. ESG news analysis using news big data: Focusing on topic
modeling analysis.-
3. Effects of the Perceived Benefit and Innovativeness of
Live Commerce on Intention to Use: Focus on Chinese consumers.-
4. A Study on
the Effect of Customer Experience on the Intention to Continuously Use Coffee
Store Mobile App based on UTAUT Model.-
5. A Study on Parallel Recommender
System with Stream Data Using Stochastic Gradient Descent.-
6. Using
Incremental Algorithm in Hybrid Recommender System Combined Sentiment
Analysis.-
7. A Bottom-Up Generic Probabilistic Building and Enriching
approach for knowledge graph using the LDA-based clustering method.-
8.
Measuring the Effects of Signal-To-Noise in EEG Emotion Recognition.-
9. Phishy? Detecting Phishing Emails Using Machine Learning and Natural
Language Processing.-
10. Are We Aware? An Empirical Study on the Privacy and
Security Awareness of Smartphone Sensors, etc.