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Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence

About Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence

Artificial intelligence (AI) is influencing the future of almost every sector and human being. AI has been the primary driving force behind emerging technologies such as big data, blockchain, robots, and the internet of things (IoT), and it will continue to be a technological innovator for the foreseeable future. New algorithms in AI are changing business processes and deploying AI-based applications in various sectors. The Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence is a comprehensive reference that presents cases and best practices of AI and knowledge engineering applications on business intelligence. Covering topics such as deep learning methods, face recognition, and sentiment analysis, this major reference work is a dynamic resource for business leaders and executives, IT managers, AI scientists, students and educators of higher education, librarians, researchers, and academicians.

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  • Language:
  • English
  • ISBN:
  • 9781668465196
  • Binding:
  • Hardback
  • Pages:
  • 388
  • Published:
  • April 3, 2023
  • Dimensions:
  • 221x25x286 mm.
  • Weight:
  • 1235 g.
Delivery: 2-3 weeks
Expected delivery: December 13, 2024

Description of Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence

Artificial intelligence (AI) is influencing the future of almost every sector and human being. AI has been the primary driving force behind emerging technologies such as big data, blockchain, robots, and the internet of things (IoT), and it will continue to be a technological innovator for the foreseeable future. New algorithms in AI are changing business processes and deploying AI-based applications in various sectors. The Handbook of Research on AI and Knowledge Engineering for Real-Time Business Intelligence is a comprehensive reference that presents cases and best practices of AI and knowledge engineering applications on business intelligence. Covering topics such as deep learning methods, face recognition, and sentiment analysis, this major reference work is a dynamic resource for business leaders and executives, IT managers, AI scientists, students and educators of higher education, librarians, researchers, and academicians.

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