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15 Utilizing AI technologies to enhance e-commerce business operations

  • S. Rajeshwari , D. Praveenadevi , S. Revathy und S. P. Sreekala
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Abstract

E-commerce has become an increasingly important sector for businesses, offering customers convenient and fast access to goods and services. With the proliferation of technological advancement, particularly Artificial intelligence (AI) technology, e-commerce continues to develop and evolve. AI technologies such as machine and deep learning can be utilized to enhance e-commerce operations. Companies can employ AI-based solutions for personalized product recommendations, automated customer service, optimized search and user interfaces, and improved security. By utilizing AI technologies, e-commerce companies can improve customer experiences, reduce operational costs, and make business operations more efficient.

Abstract

E-commerce has become an increasingly important sector for businesses, offering customers convenient and fast access to goods and services. With the proliferation of technological advancement, particularly Artificial intelligence (AI) technology, e-commerce continues to develop and evolve. AI technologies such as machine and deep learning can be utilized to enhance e-commerce operations. Companies can employ AI-based solutions for personalized product recommendations, automated customer service, optimized search and user interfaces, and improved security. By utilizing AI technologies, e-commerce companies can improve customer experiences, reduce operational costs, and make business operations more efficient.

Kapitel in diesem Buch

  1. Frontmatter I
  2. Preface V
  3. Contents VII
  4. List of authors IX
  5. About the editors XIII
  6. 1 Introduction to artificial intelligence 1
  7. 2 AI technologies, tools, and industrial use cases 21
  8. 3 Classification and regression algorithms 53
  9. 4 Clustering and association algorithm 87
  10. 5 Reinforcement learning 109
  11. 6 Evaluation of AI model performance 125
  12. 7 Methods of cross-validation and bootstrapping 145
  13. 8 Meta-learning through ensemble approach: bagging, boosting, and random forest strategies 167
  14. 9 AI: issues, concerns, and ethical considerations 189
  15. 10 The future with AI and AI in action 213
  16. 11 A survey of AI in industry: from basic concepts to industrial and business applications 233
  17. 12 The intelligent implications of artificial intelligence-driven decision-making in business management 251
  18. 13 An innovative analysis of AI-powered automation techniques for business management 269
  19. 14 The smart and secured AI-powered strategies for optimizing processes in multi-vendor business applications 287
  20. 15 Utilizing AI technologies to enhance e-commerce business operations 309
  21. 16 Exploring the potential of artificial intelligence in wireless sensor networks 331
  22. 17 Exploring artificial intelligence techniques for enhanced sentiment analysis through data mining 345
  23. 18 Exploring the potential of artificial intelligence for automated sentiment 361
  24. 19 A novel blockchain-based artificial intelligence application for healthcare automation 373
  25. 20 Enhancing industrial efficiency with AI-enabled blockchain-based solutions 387
  26. Index 401
Heruntergeladen am 3.12.2025 von https://www.degruyterbrill.com/document/doi/10.1515/9783111323749-015/html?lang=de
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