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Role of Explainable Artificial Intelligence in E-Commerce

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Role of Explainable Artificial Intelligence in E-Commerce Role of Explainable Artificial Intelligence in E-Commerce

出版社:Springer
出版日期:2024-04-26
語言:英文   規格:精裝 / 290頁 / 普通級/ 初版
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圖書名稱:Role of Explainable Artificial Intelligence in E-Commerce

內容簡介

The technological boom has provided consumers with endless choices, removing the hindrance of time and place. Understanding the dynamic and competitive business environment, marketers know they need to reinforce indestructible customer experience with the support of algorithmic configurations to minimize human intrusion. World Wide Web (WWW) and online marketing have changed the way of conducting business; with artificial intelligence (AI), business houses can furnish a customized experience to fulfil the perceived expectation of the customer.

Artificial intelligence bridges the gap between business and prospective clients, provides enormous amounts of information, prompts grievance redressal system, and further complements the client’s preference. The opportunities online marketing offers with the blend of artificial intelligence tools like chatbots, recommenders, virtual assistance, and interactive voice recognition create improved brand awareness, better customer relationshipmarketing, and personalized product modification.

Explainable AI provides the subsequent arena of human-machine collaboration, which will complement and support marketers and people so that they can make better, faster, and more accurate decisions. According to PwC’s report on Explainable AI(XAI), AI will have $15.7 trillion of opportunity by 2030. However, as AI tools become more advanced, more computations are done in a "black box" that humans can hardly comprehend. But the rise of AI in business for actionable insights also poses the following questions: How can marketers know and trust the reasoning behind why an AI system is making recommendations for action? What are the root causes and steering factors? Thus, transparency, trust, and a good understanding of expected business outcomes are increasingly demanded.

 

作者簡介

Dr Loveleen Gaur is currently working as a Professor of Artificial Intelligence and Data Analytics at Amity International Business School, Amity University, India. She is also an adjunct professor with Taylor University, Malaysia & University of South Pacific, Fiji. she demonstrates noteworthy expertise in Artificial Intelligence, as well as the scientific knowledge and technical skills in developing state-of-the-art AI solutions for business and healthcare challenges to improve the commercial efficiency and clinical efficacy of AI-driven technology. She is a senior IEEE member and Series Editor with CRC and Wiley. Prof. Gaur has significantly contributed to enhancing scientific understanding by participating in over three hundred scientific conferences, symposia, and seminars, chairing technical sessions and by delivering plenary and invited talks. Prof Gaur is a global keynote speaker for several IEEE international conferences, external examiner/evaluator for PhD, Guest editor of several reputed journals, the editorial board of several research journals, and an active member of respected conferences around the globe.

Dr. Ajith Abraham is the current Dean of the Faculty of Computing and Data Sciences at FLAME University, India. He is also a Professor of Artificial Intelligence. He is the Founding Director of Machine Intelligence Research Labs, a not-for-profit Scientific Network for Innovation and Research Excellence connecting industry and academia. The Network with HQ in Seattle, USA has currently more than 1,500 scientific members from over 105 countries. As an Investigator / Co-Investigator, he has won research grants worth over 100+ Million US$. He has over 33 years of industry and academic experience. His primary research is on developing advanced machine intelligence using hybridization of function approximation methods, approximate reasoning and global optimization methods focused on big data analytics, understanding networks, information security, Web intelligence, decision support systems, the Internet of Things, etc.

He has authored or co-authored more than 1,400 research publications out of which there are 100+ books covering various aspects of Computer Science. One of his books was translated to Japanese and few other articles were translated to Russian and Chinese. Dr. Abraham has more than 50,000+ academic citations (h-index of 105+ as per google scholar). He has given more than 150 plenary lectures and conference tutorials (in 20+ countries). Dr. Abraham was the Chair of IEEE Systems Man and Cybernetics Society Technical Committee on Soft Computing (which has over 200+ members) during 2008-2021 and served as a Distinguished Lecturer of IEEE Computer Society representing Europe (2011-2013). Dr. Abraham was the editor-in-chief of Engineering Applications of

Artificial Intelligence (EAAI) during 2016-2021 and serves/served the editorial board of over 15 International Journals indexed by Thomson ISI. He received Ph.D. in Computer Science from Monash University, Melbourne, Australia (2001) and a Master of Science degree in Control and Automation from Nanyang Technological University, Singapore. He holds a Bachelor’s Degree in Electrical and Electronic Engineering from the University of Calicut, India.

 

詳細資料

  • ISBN:9783031556142
  • 規格:精裝 / 290頁 / 普通級 / 初版
  • 出版地:美國
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