Relevant bibliographies by topics / Quantum Personalization

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Quantum Personalization'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Quantum Personalization"

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Chen, Anyi. "Application of Quantum Computing Technology in the Optimization of Search Sorting for Fashion E-commerce." Journal of Computer Science and Artificial Intelligence 2, no. 2 (2025): 8–11. https://doi.org/10.54097/spk64b71.

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With the continuous progress of the fashion e-commerce industry, consumers' demand for accuracy and personalization of search results is increasing day by day. However, traditional computing methods are inadequate in dealing with big data processing and complex sorting tasks. Quantum computing, with its unique advantages in solving complex problems and parallel operations, has gradually become a research hotspot for improving search ranking optimization. This article explores various challenges encountered in applying quantum computing to the search ranking process of fashion e-commerce platfo
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Chinnaraju, Arunraju. "Quantum Computing in Consumer Behavior: A Theoretical Framework for Market Prediction and Decision Analytics." International Journal of Advanced Research in Science, Communication and Technology 5, no. 2 (2025): 339–71. https://doi.org/10.48175/ijarsct-23352.

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<strong>This is the author-archived version of the article titled</strong><em>&ldquo;Quantum Computing in Consumer Behavior: A Theoretical Framework for Market Prediction and Decision Analytics&rdquo;</em>,published in <em>International Journal of Advanced Research in Science, Communication and Technology (IJARSCT)</em>, Vol. 5, Issue 2, February 2025. The official published version is available at: https://doi.org/10.48175/IJARSCT-23352 URL: https://ijarsct.co.in/Paper23352.pdf This version has been deposited on Zenodo to enhance academic visibility and ensure indexing through scholarly datab
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Jeyaraman, Naveen, Madhan Jeyaraman, and Swaminathan Ramasubramanian. "Quantum Leap: Envisioning the Role of Quantum Computing in Orthopedic Practice." Journal of Orthopaedic Case Reports 14, no. 7 (2024): 1–5. http://dx.doi.org/10.13107/jocr.2024.v14.i07.4552.

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Quantum computing represents a significant paradigm shift in our approach to processing information by leveraging the enigmatic principles of quantum mechanics. This cutting-edge technology is designed to perform computational tasks at exponentially higher speeds compared to classical computing, offering potential breakthroughs in fields as diverse as cryptography, financial modeling, and scientific research [1]. In the realm of scientific research, particularly, quantum computing promises to transform the capabilities for complex data analysis and modeling, crucial for advancements in various
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Praveen Kumar Reddy Bandi. "AI-driven personalization in wealth management: Redefining client engagement and advisory services." World Journal of Advanced Engineering Technology and Sciences 15, no. 3 (2025): 795–802. https://doi.org/10.30574/wjaets.2025.15.3.1014.

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The wealth management industry is undergoing a fundamental transformation driven by artificial intelligence and machine learning technologies. This article explores how AI-enabled personalization is reshaping traditional approaches to client engagement and investment advisory services. As digital natives comprise an increasing proportion of wealth management clients, the demand for hyper-personalized experiences has accelerated, shifting away from standardized offerings toward data-driven approaches that deliver tailored investment strategies and communication across multiple channels. The app
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Sanath Chilakala. "Next-Gen Transformation of Insurance Document Management." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 2644–51. https://doi.org/10.32628/cseit251112277.

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The integration of Artificial Intelligence in the insurance industry's document and letter generation processes marks a transformative advancement in operational efficiency. This technical article examines the comprehensive implementation of AI technologies across various aspects of insurance documentation, including policy generation, claims processing, and customer correspondence. The article analyzes the architectural framework, focusing on Natural Language Processing and Machine Learning components that form the backbone of modern insurance systems. The article demonstrates how AI-driven s
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Sun, Libo, and Dongjin Fu. "A Review of Machine Learning-Based Recommendation Algorithms in Information Technology Systems." Journal of Computer, Signal, and System Research 2, no. 2 (2025): 1–27. https://doi.org/10.71222/gvtd3173.

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This review explores the evolving landscape of recommendation systems, focusing on the integration of machine learning techniques to enhance personalization and effectiveness. It high-lights various approaches, including content-based filtering, collaborative filtering, and hybrid models, while examining the role of advanced machine learning methods such as deep learning and reinforcement learning. The discussion addresses the challenges faced by current algorithms, including data sparsity, scalability issues, and biases. Future directions for research are proposed, emphasizing the integration
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Dahnial, Irfan, Al-Khowarizmi Al-Khowarizmi, and Karina Winda. "Development of learning models based on machine learning with quantum annealing for learning optimization in the digital era." Eastern-European Journal of Enterprise Technologies 3, no. 2 (135) (2025): 65–72. https://doi.org/10.15587/1729-4061.2025.333721.

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The object of this study is the prediction of digital learning achievement. The problems solved in this study are the low accuracy and efficiency of the prediction model caused by the complexity of the learning data and the limitations of conventional tuning methods such as grid search and random search which are unable to optimally navigate the wide and non-linear parameter space. The results obtained show that the integration of quantum annealing into the hyperparameter optimization process can significantly improve model performance. Model accuracy increased from 82% to 91%, with consistent
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Deepika Bhatia. "GenAI Chips in Cloud Data Centers: Driving Efficiency at Scale." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 3891–97. https://doi.org/10.32628/cseit25112705.

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Integrating Generative AI (GenAI) chips in cloud data centers marks a transformative advancement in managing artificial intelligence workloads and computational efficiency. This comprehensive article explores the revolutionary impact of these specialized processors on cloud infrastructure, focusing on three key areas: advanced cooling technologies, power management innovations, and applications in cloud computing. It examines how liquid cooling systems and immersion cooling technologies are revolutionizing thermal management in data centers while Dynamic Voltage Scaling (DVS) systems are optim
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Jain, K. K. "Role of Nanobiotechnology in Developing Personalized Medicine for Cancer." Technology in Cancer Research & Treatment 4, no. 6 (2005): 645–50. http://dx.doi.org/10.1177/153303460500400608.

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Personalized medicine simply means the prescription of specific therapeutics best suited for an individual. Personalization of cancer therapies is based on a better understanding of the disease at the molecular level. Nanotechnology will play an important role in this area. Nanobiotechnology is being used to refine discovery of biomarkers, molecular diagnostics, drug discovery and drug delivery, which are important basic components of personalized medicine and are applicable to management of cancer as well. Examples are given of the application of quantum dots, gold nanoparticles, and molecula
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Vikram Sai Prasad Karnam. "AI Transformation in the Airline Industry: Technical Perspectives." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 1828–34. https://doi.org/10.30574/wjarr.2025.26.2.1798.

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Artificial intelligence technologies are transforming airline operations, delivering significant enhancements in operational efficiency, cost reduction, and passenger experience. The aviation sector has witnessed widespread adoption of sophisticated AI applications across critical business functions. From dynamic pricing algorithms that adjust fares based on real-time competitive intelligence to natural language processing systems that enable responsive customer support, these technologies have evolved from experimental prototypes to operational capabilities. Revenue management systems leverag
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Dissertations / Theses on the topic "Quantum Personalization"

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Zhang, Peng. "Approximating true relevance model in relevance feedback." Thesis, Robert Gordon University, 2013. http://hdl.handle.net/10059/808.

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Relevance is an essential concept in information retrieval (IR) and relevance estimation is a fundamental IR task. It involves not only document relevance estimation, but also estimation of user's information need. Relevance-based language model aims to estimate a relevance model (i.e., a relevant query term distribution) from relevance feedback documents. The true relevance model should be generated from truly relevant documents. The ideal estimation of the true relevance model is expected to be not only effective in terms of mean retrieval performance (e.g., Mean Average Precision) over all
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Book chapters on the topic "Quantum Personalization"

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Jadhav, Babasaheb, Ashish Kilkarni, Pooja Kulkarni, and Shashi Kant Gupta. "Generative AI." In Advances in Computer and Electrical Engineering. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5762-0.ch002.

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This chapter explores how generative AI achieves content personalization, its implications for user engagement and satisfaction, and the potential challenges and ethical considerations associated with its widespread adoption. The purpose is to examine the role of generative artificial intelligence (AI) in facilitating content personalization within the Metaverse by exploring how Generative AI shapes user experiences. To do this, the chapter evaluates the strengths and weaknesses of quantum computing and blockchain technologies. It creates hypothetical scenarios illustrating the potential impac
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Semwal, Rajeev, Pankaj Kumar Tyagi, Nandita Tripathi, and Udit Kumar Pandey. "Navigating the Data-Driven Future of Virtual and Hybrid Events." In Advances in Hospitality, Tourism, and the Services Industry. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2272-7.ch019.

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Data analytics is transforming virtual and hybrid event planning with quantifiable goals, real-time analytics, and many data sources. Modern technologies like emotional analytics, AI-driven predictive analytics, quantum computing, and others boost customization, engagement, and event immersion. Extended reality (XR) analytics, edge AI, and hyper-personalization provide unmatched participant experiences. An analytical attitude, coordinated leadership, and extensive team training are necessary. Participants' privacy is protected by data security and ethics. Data analytics affects decision-making
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Ghodake, Shamrao Parashram, Jaya Saxena, Nitesh Behare, et al. "Strategic Significance of Machine Learning in Financial Services." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-0209-6.ch014.

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Machine learning (ML) is transforming the financial services industry by driving innovation in fraud detection, risk management, customer personalization, and more. This chapter explores the strategic significance of ML, its key applications, and future trends shaping its adoption. Integration with blockchain technology enhances security and automation, while advancements in quantum computing promise faster, more accurate financial models. However, challenges such as data privacy, algorithmic bias, and regulatory compliance persist. The evolution of regulatory frameworks and the growing import
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Ghosn, Fadi. "Artificial Intelligence in Investment and Wealth Management." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-0129-7.ch001.

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This chapter examines the transformative role of artificial intelligence (AI) in investment and wealth management, emphasizing its impact on decision-making, portfolio management, financial service personalization, and sustainable finance. It contrasts traditional investment methods with AI-driven strategies such as algorithmic trading, robo-advisors, and predictive analytics. The chapter explores AI's role in portfolio diversification, risk management, and tailored investment solutions, highlighting advancements in machine learning and natural language processing. AI-powered sentiment analysi
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Rane, Jayesh, Ömer Kaya, Suraj Kumar Mallick, and Nitin Liladhar Rane. "Future Research Opportunities for Artificial Intelligence in Industry 4.0 and 5.0." In Future Research Opportunities for Artificial Intelligence in Industry 4.0 and 5.0. Deep Science Publishing, 2024. http://dx.doi.org/10.70593/978-81-981271-0-5.

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Artificial intelligence (AI), machine learning (ML) and other emerging technologies such as cloud, edge and quantum computing are converging to rewrite the landscape of modern industries and society as a whole. Comprehensive in scope, the book offers a detailed account of these inter-related domains current trends and future possibilities. Chapter 1: We begin by setting the stage with an overview on various trends, problems proposed to solve and road ahead provided by AI, Machine Learning and Deep learning from cloud, edge and quantum computing perspectives. The same is a comprehensive summary
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Laptiev, Sergii, Iryna Mazur, Yana Koval, and Mykhailo Laptiev. "Business Reputation and Resilience: Digital Skill Strategies in a Transformative Era." In Digital Skills in a Digital Society: Requirements and Challenges. Scientific Center of Innovative Research, 2024. https://doi.org/10.36690/dsds-189-209.

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In the digital transformation era, businesses must prioritize the development of employees' digital skills to maintain competitiveness and enhance their reputation. With artificial intelligence (AI) revolutionizing industries, organizations face the dual challenge of leveraging technology and addressing workforce readiness. This chapter explores how investing in digital skills contributes to improved customer experiences, innovation, and stronger stakeholder relationships, positioning businesses as leaders in a rapidly evolving digital economy. The research aims to identify the critical role o
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Conference papers on the topic "Quantum Personalization"

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De Carolis, Berardina Nadja, Corrado Loglisci, Maria Grazia Miccoli, Giuseppe Palestra, and Sergio Violante. "Quantum-Enhanced Social Robotics: The QUADRI Project." In UMAP '25: 33rd ACM Conference on User Modeling, Adaptation and Personalization. ACM, 2025. https://doi.org/10.1145/3708319.3735545.

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Journal articles
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