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Relevant bibliographies by topics / AI-driven personalization

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Academic literature on the topic 'AI-driven personalization'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "AI-driven personalization"

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Singh, Navdeep. "AI-Driven Personalization in eCommerce Advertising." International Journal for Research in Applied Science and Engineering Technology 11, no. 12 (2023): 1692–98. http://dx.doi.org/10.22214/ijraset.2023.57695.

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Abstract: In the dynamic realm of eCommerce, the integration of Artificial Intelligence (AI) has revolutionized advertising strategies, forging a path towards highly personalized consumer experiences. This exploration delves into the multifaceted role of AI in eCommerce advertising, highlighting the efficacy of technologies such as machine learning, natural language processing, and predictive analytics. A thorough analysis of consumer behavior, underpinned by AI, reveals advancements in data collection, privacy concerns, and innovative data analysis techniques. Ethical considerations, includin

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Enoch, Oluwademilade Sodiya, Oladipupo Amoo Olukunle, Joseph Umoga Uchenna, and Atadoga Akoh. "AI-driven personalization in web content delivery: A comparative study of user engagement in the USA and the UK." World Journal of Advanced Research and Reviews 21, no. 2 (2024): 887–902. https://doi.org/10.5281/zenodo.14008497.

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In the ever-evolving landscape of digital experiences, AI-driven personalization has emerged as a pivotal force shaping how users interact with web content. This study conducts a comparative analysis of AI-driven personalization strategies in web content delivery, focusing on user engagement in the United States (USA) and the United Kingdom (UK). The research delves into the nuanced ways in which AI algorithms tailor web content to individual user preferences, examining the impact on user engagement metrics such as time spent on site, click-through rates, and conversion rates. Through a meticu

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Mahaboobsubani, Shaik. "AI-Driven Personalization in Hospitality Booking Platforms." Journal of Scientific and Engineering Research 8, no. 10 (2021): 223–30. https://doi.org/10.5281/zenodo.14356522.

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The use of AI in the hospitality sector has moved booking platforms into a direction of offering extremely personalized experiences. The article discusses how AI-driven recommendation systems produce booking options tailored to user preferences as a way to further increase engagement and user satisfaction. Different machine learning models are investigated to assess the effectiveness in predicting user behavior and preference, including collaborative filtering, content-based filtering, and hybrid approaches. Comparative studies indicate that the level of engagement and booking conversion is si

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Enoch Oluwademilade Sodiya, Olukunle Oladipupo Amoo, Uchenna Joseph Umoga, and Akoh Atadoga. "AI-driven personalization in web content delivery: A comparative study of user engagement in the USA and the UK." World Journal of Advanced Research and Reviews 21, no. 2 (2024): 887–902. http://dx.doi.org/10.30574/wjarr.2024.21.2.0502.

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In the ever-evolving landscape of digital experiences, AI-driven personalization has emerged as a pivotal force shaping how users interact with web content. This study conducts a comparative analysis of AI-driven personalization strategies in web content delivery, focusing on user engagement in the United States (USA) and the United Kingdom (UK). The research delves into the nuanced ways in which AI algorithms tailor web content to individual user preferences, examining the impact on user engagement metrics such as time spent on site, click-through rates, and conversion rates. Through a meticu

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Verma, Shruti, and Dr Sabeeha Fatma. "How Personalization and AI Are Transforming Digital Marketing Campaigns." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42751.

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In the rapidly evolving digital marketing landscape, personalization and artificial intelligence (AI) have emerged as transformative forces, revolutionizing how brands engage with their audiences. This paper explores the integration of AI-driven personalization in digital marketing campaigns, highlighting its impact on consumer experience, brand loyalty, and overall campaign effectiveness. AI-powered algorithms leverage vast amounts of data to analyze consumer behavior, preferences, and purchasing patterns, enabling brands to deliver highly relevant content, product recommendations, and target

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Nnenna Ijeoma Okeke, Olufunke Anne Alabi, Abbey Ngochindo Igwe, Onyeka Chrisanctus Ofodile, and Chikezie Paul-Mikki Ewim. "AI-driven personalization framework for SMES: Revolutionizing customer engagement and retention." World Journal of Advanced Research and Reviews 24, no. 1 (2024): 2019–35. http://dx.doi.org/10.30574/wjarr.2024.24.1.3208.

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In today's competitive business landscape, Small and Medium Enterprises (SMEs) face unique challenges in building and maintaining strong customer relationships. An AI-driven personalization framework offers a transformative solution by enabling SMEs to deliver highly targeted and individualized customer experiences, improving both engagement and retention rates. This review outlines how artificial intelligence (AI) can empower SMEs by integrating data-driven insights with customer interaction processes to revolutionize business practices. AI-driven personalization leverages machine learning al

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Nnenna, Ijeoma Okeke, Anne Alabi Olufunke, Ngochindo Igwe Abbey, Chrisanctus Ofodile Onyeka, and Paul-Mikki Ewim Chikezie. "AI-driven personalization framework for SMES: Revolutionizing customer engagement and retention." World Journal of Advanced Research and Reviews 24, no. 1 (2024): 2019–35. https://doi.org/10.5281/zenodo.15051414.

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In today's competitive business landscape, Small and Medium Enterprises (SMEs) face unique challenges in building and maintaining strong customer relationships. An AI-driven personalization framework offers a transformative solution by enabling SMEs to deliver highly targeted and individualized customer experiences, improving both engagement and retention rates. This review outlines how artificial intelligence (AI) can empower SMEs by integrating data-driven insights with customer interaction processes to revolutionize business practices. AI-driven personalization leverages machine learning al

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Thajchayapong, Ploy, and Ashok K. Goel. "Personalized Learning through AI-Driven Data Pipeline." Proceedings of the AAAI Symposium Series 5, no. 1 (2025): 111–14. https://doi.org/10.1609/aaaiss.v5i1.35572.

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The integration of artificial intelligence (AI) in education holds significant promise for transforming personalized learning. By analyzing student learning data, AI systems can adapt instruction to meet individual needs through tailored content, adaptive learning paths, real-time feedback, and continuous improvement loops. However, effective personalization at scale demands not only access to large volumes of learner data but also robust data architectures to collect, organize, standardize, and analyze that data in a secure and meaningful way. However, note that the ability of AI to personali

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Mandagie, Wenny Candra, and Robert Kristaung. "The power of AI personalization: Mediated moderation in social & e-commerce." Jurnal Manajemen dan Pemasaran Jasa 18, no. 1 (2025): 35–58. https://doi.org/10.25105/v18i1.21587.

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This study investigates the impact of AI-driven personalization on key customer outcomes within Indonesia's e-commerce landscape. It examines how personalization influences customer engagement, trust, perceived relevance, customer experience, and purchase frequency. While prior studies have extensively explored AI personalization, limited research has examined its mediated moderation effects on customer behavior in emerging e-commerce markets, particularly in Indonesia. This study addresses the gap by analyzing the moderating effect of education level and the mediating role of perceived releva

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Suresh Kumar Maddala. "AI-driven personalization in consumer goods and retail: A technical analysis." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 458. https://doi.org/10.30574/wjarr.2025.26.2.1639.

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AI-driven personalization has become a critical competitive advantage in modern retail environments, enabling tailored customer experiences across digital and physical touchpoints. This article explores the transformative role of artificial intelligence technologies in reshaping consumer goods and retail personalization strategies. Beginning with an overview of fundamental AI personalization technologies, the discussion progresses through advanced recommendation engine architectures, dynamic pricing implementations, conversational AI systems, and in-store personalization solutions. The article

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Book chapters on the topic "AI-driven personalization"

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Vallabhaneni, Anirudh Sai, Anjali Perla, Revanth Reddy Regalla, and Neelam Kumari. "The Power of Personalization: AI-Driven Recommendations." In Minds Unveiled. Productivity Press, 2024. https://doi.org/10.4324/9781032711089-9.

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Mondal, Hirak, Anindya Nag, Md Mushfiqur Rahman, and Anupam Kumar Bairagi. "Interpreting Electroencephalogram Brain Signals: Insights from AI-driven Analysis." In Brain Networks in Neuroscience: Personalization Unveiled Via Artificial Intelligence. River Publishers, 2025. https://doi.org/10.1201/9788770047371-12.

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Kumar, A. V. Senthil, M. Mosikan, Amit Dutta, et al. "AI-Driven Personalization in Tourism." In Advances in Hospitality, Tourism, and the Services Industry. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5678-4.ch002.

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This chapter delves into the transformative impact of artificial intelligence (AI) technologies on the tourism sector, focusing on personalized and sustainable travel experiences. It explores how AI-driven recommendation systems, chatbots, and predictive analytics revolutionize personalization by analyzing vast datasets to tailor travel recommendations based on individual preferences. The chapter also addresses challenges such as data privacy and ethical considerations, emphasizing the need for responsible AI implementation. Looking ahead, the chapter underscores the potential for further AI-d

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Suresh, D., P. Lokesh, B. Yamini, et al. "AI Driven Personalization in Education." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-8744-3.ch002.

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Education systems adopting technological solutions, Artificial Intelligence (AI) is making its ways into becoming a game changer in delivering learner centered approaches to learning. This questionnaire focuses on the promotion of effective learning plans using artificial intelligence to improve learning experiences as they are made to suit the learner. They are adaptive learning system which change content on the basis of performance, intelligent tutor system, and big data analytical system which provides solutions. Those include machine learning, NLP, and computer vision technologies that pl

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Balcıoğlu, Yavuz Selim. "AI-Driven Personalization in Omnichannel Marketing." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5340-0.ch004.

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This chapter explores the transformative role of AI-driven personalization in omnichannel marketing, emphasizing its importance in enhancing customer engagement and loyalty. It begins by defining omnichannel marketing and tracing its evolution from traditional to digital channels. The chapter explores into key components of AI-driven personalization, including data collection and analysis, customer segmentation, predictive analytics, and real-time personalization. Implementation strategies are discussed, highlighting the integration of AI tools, data management, and the design of personalized

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Coelho, Maria Carolina Cordeiro Dias, and Irma Imamović. "AI-Driven Personalization in Beauty Retail." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5340-0.ch005.

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This study explores the evolving beauty industry transformed by technology, focusing on how personalized artificial intelligence (AI) shapes customer experience, satisfaction, and loyalty in online beauty shopping. Through semi-structured interviews with 10 Portuguese female online buyers aged 18-30, it reveals the importance of understanding and meeting customer preferences in a fast-paced digital environment. The research highlights the crucial role of personal experiences and trust in influencing customer satisfaction and loyalty. It examines the impact of AI-based recommendations and inter

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Mishra, Shreeansh, Mansurali Anifa, and Jigisha Naidu. "AI-Driven Personalization in Tourism Services." In Advances in Hospitality, Tourism, and the Services Industry. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-7388-0.ch001.

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The rapid advancement of artificial intelligence (AI) is transforming the global tourism industry, offering new opportunities for service personalization and enhanced customer experiences. AI-driven personalization is rapidly reshaping the tourism industry by tailoring services to meet individual customer preferences. In India, this technological advancement is particularly impactful, offering significant potential to improve tourist satisfaction and business performance. This research article investigates the Impact of AI-driven personalization on the tourism industry in India, focusing on ho

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Manoj, G., P. Arockia Juliet, V. S. Mege, K. V. Geetha Devi, Chandramowleeswaran Gnanasekaran, and P. Indira. "AI for Personalization." In Practical Applications of Self-Service Technologies Across Industries. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-4667-0.ch010.

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In the age of rapid technological advancement, Artificial Intelligence (AI) is reshaping customer experiences by enabling highly personalized interactions in self-service technologies. This chapter explores the transformative impact of AI-driven personalization on customer journeys, focusing on how machine learning algorithms, predictive analytics, and natural language processing (NLP) are redefining self-service systems across industries such as retail, banking, healthcare, and hospitality. By analyzing customer data in real time, AI-powered systems tailor recommendations, streamline decision

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Jindal, Priyanshi, and Harshit Gouri. "AI-Personalization Paradox." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1918-5.ch004.

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The integration of AI into various aspects of our lives has significantly reshaped how we access information, products, and services. AI-driven personalization, a key feature of many platforms, aims to enhance user experiences by tailoring content to individual preferences. Advancement of AI personalization has given rise to the filter bubble and echo-chamber phenomena. Filter bubbles expose consumers to content that reinforces their existing beliefs and preferences, creating a paradox. This chapter explores the multifaceted implications of AI-personalization paradox on digital consumer behavi

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Kaperonis, Stavros. "AI-Powered Personalization." In Advances in Marketing, Customer Relationship Management, and E-Services. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-3799-8.ch013.

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Marketing landscape experiencing a drastic change, driven by the growth of artificial intelligence (AI) and personalization, replacing "one-size-fits-all" marketing approach by more personalized marketing strategies, like machine learning and predictive analysis. This will allow organisations to engage with users in a dynamic, user-specific design, thus enhancing user engagement and satisfaction. Platforms such as Netflix, Amazon, and Spotify, already use artificial intelligence to tailor content and recommendations based on user behaviour patterns, ensuring user retention and high loyalty. Th

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Conference papers on the topic "AI-driven personalization"

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Shakhov, Denis, Ruslan Batashev, and Ilyos Abdullayev. "AI-Driven Personalization in Organizational Communication." In 2025 Communication Strategies in Digital Society Seminar (ComSDS). IEEE, 2025. https://doi.org/10.1109/comsds65569.2025.10971302.

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Parasar, Deepa, Swetta Kukreja, Vedang Vaidya, Shweta Pillai, Rochelle Maria Anthony, and Shrilesh Rane. "Spotlight : Redefining Theatre Application Through AI-Driven Personalization and Community Engagement." In 2024 IEEE 4th International Conference on ICT in Business Industry & Government (ICTBIG). IEEE, 2024. https://doi.org/10.1109/ictbig64922.2024.10911220.

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Zhang, Jiaxin, Pavan Kumar Murugan, Lin Chen, et al. "THE DEVELOPMENT OF SMART WARDROBE: AI-DRIVEN PERSONALIZATION IN E-COMMERCE." In 17th International Conference on Education and New Learning Technologies. IATED, 2025. https://doi.org/10.21125/edulearn.2025.1842.

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Ramzan, Hafiz Arslan, Fatima Abdulah, Muddaber Ahmad, Sadia Ramzan, and Munazza Ashraf. "AI-Driven Personalization of E-Therapy Interventions for Anxiety, Stress, and Depression." In 2024 18th International Conference on Open Source Systems and Technologies (ICOSST). IEEE, 2024. https://doi.org/10.1109/icosst64562.2024.10871158.

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Shukla, Vinit Kumar, and Seshaiah Merikapudi. "Adaptive Learning Revolution with AI-Driven Personalization and Gamified Real-Time Interaction." In 2025 International Conference on Knowledge Engineering and Communication Systems (ICKECS). IEEE, 2025. https://doi.org/10.1109/ickecs65700.2025.11034830.

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Ganeshkumar, M., S. Karunakaran, R. Muzhumathi, and R. Suguna. "AI-Driven Marketing Insights: Harnessing Machine Learning for Enhanced Consumer Engagement and Personalization." In 2024 First International Conference on Software, Systems and Information Technology (SSITCON). IEEE, 2024. https://doi.org/10.1109/ssitcon62437.2024.10796558.

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Matharu, Harmeet, Zameer Pasha, Mohd Aarif, L. Natrayan, S. Kaliappan, and I. Infant Raj. "Developing an AI-Driven Personalization Engine for Real-Time Content Marketing in E-commerce Platforms." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725400.

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Arora, Amishi, Rahul Kapale, Pratyush Sharma, Maitreya Nalavade, Mubina Saifee, and Manda Ukey. "The Impact of AI-Driven Personalization on Customer Loyalty: A Meta-Analysis of E-commerce Studies." In 2024 2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry (IDICAIEI). IEEE, 2024. https://doi.org/10.1109/idicaiei61867.2024.10842906.

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Patil, Shalmali, Aparna Bhat, Nilesh Jain, and Vishal Javalkar. "Integrating Research on AI-Driven Hyper-Personalization: A Review and Framework for Scalable Social Media Campaigns." In 2025 International Conference on Pervasive Computational Technologies (ICPCT). IEEE, 2025. https://doi.org/10.1109/icpct64145.2025.10940951.

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Somantri, Dihak Muhammad Nur Al-Ma'arif, Afrizal Maulana, Risa Aidha, Imam Sanjaya, and Anggun Fergina. "AI-Driven Curriculum Personalization System Using K-Nearest Neighbors Algorithm Based on Psychological Profiles and Interests." In 2024 10th International Conference on Computing, Engineering and Design (ICCED). IEEE, 2024. https://doi.org/10.1109/icced64257.2024.10983409.

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Reports on the topic "AI-driven personalization"

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Pasupuleti, Murali Krishna. AI-Driven Marketing Innovations: Personalization and Ethics in the Digital Era. National Education Services, 2025. https://doi.org/10.62311/nesx/rr625.

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Abstract: This article explores the transformative impact of artificial intelligence (AI) on digital marketing, focusing on strategies for delivering personalized content and ensuring ethical advertising. By leveraging AI, marketers can now analyze consumer behavior with precision, enabling targeted content, automated ad placement, and real-time adjustments that enhance user engagement and conversions. The Article examines foundational AI techniques, such as recommendation engines, predictive analytics, and natural language processing, which drive personalization at scale. Additionally, it add

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