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- Vol. 5 Issue 3
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Device Wizard: Your ultimate buying companion
Authors
123 Department of Computer Science and Engineering Inderprastha Engineering College, Sahibabad, Ghaziabad, Uttar Pradesh, India. 4 Assistant Professor, Department of Computer Science and Engineering Inderprastha Engineering College, Sahibabad, Ghaziabad, Uttar Pradesh, India.
Article Information
- DOI
- No DOI
- Published In
- Volume 5, Issue 3 (2024)
- Published Online
- May-June 2024
- Pages
- 119-124
- Article Type
- Research Article
- Check for updates
- No DOI available for cross-reference
References
1. Smith,A.(2023).Opti Select: A Personalized Mobile Device Recommendation App.[Online]
2. Garcia,L.M.(2023). Smart Choice:Empower in users with intelligent mobile device recommendations.
3. Wong, S. T., Patel, R. (2023). TechPulse: Revolutionizing Device Selection Through Cutting-Edge Recommendations.
4. Johnson, K. A. (2022). InsightHub: Enhancing User Experience in Personalized Content Recommendation Systems. [Online].
5. Chen, J. Y., Rodriguez, M. (2022). DynamicSelect: A Novel Approach for Adaptive Mobile Device Recommendations in Real-Time
Environments.
6. Taylor, R. B. (2022). IntelliGadget: An AI-driven Framework for Context-Aware Mobile Device Suggestions in Smart Environments.
7. Kim, H. S., Singh, A. (2022). EvoTechAdvisor: Evolving Strategies for Intelligent Device Recommendations in a Rapidly Changing
Tech Landscape.
8. Martinez, E. P. (2022). QuantumSuggest: Harnessing Quantum Computing for Enhanced Personalized Mobile Device
Recommendations.
9. Nguyen, Q. H., Lopez, M. A. (2022). SwiftSelect: Accelerating Mobile Device Decision-Making Through Agile Recommendation
Algorithms.
10. Thompson, G. C. (2022). SynthAI: A Synergistic Approach to Artificial Intelligence-driven Mobile Device Recommendations.
11. Hernandez, P. F., Chang, W. (2022). FutureFlow: Anticipating User Preferences for Proactive Mobile Device Recommendations.
12. Lee, J. W. (2022). NexusAdvisor: Bridging the Gap Between User Preferences and Cutting-Edge Mobile Device Technologies.
2. Garcia,L.M.(2023). Smart Choice:Empower in users with intelligent mobile device recommendations.
3. Wong, S. T., Patel, R. (2023). TechPulse: Revolutionizing Device Selection Through Cutting-Edge Recommendations.
4. Johnson, K. A. (2022). InsightHub: Enhancing User Experience in Personalized Content Recommendation Systems. [Online].
5. Chen, J. Y., Rodriguez, M. (2022). DynamicSelect: A Novel Approach for Adaptive Mobile Device Recommendations in Real-Time
Environments.
6. Taylor, R. B. (2022). IntelliGadget: An AI-driven Framework for Context-Aware Mobile Device Suggestions in Smart Environments.
7. Kim, H. S., Singh, A. (2022). EvoTechAdvisor: Evolving Strategies for Intelligent Device Recommendations in a Rapidly Changing
Tech Landscape.
8. Martinez, E. P. (2022). QuantumSuggest: Harnessing Quantum Computing for Enhanced Personalized Mobile Device
Recommendations.
9. Nguyen, Q. H., Lopez, M. A. (2022). SwiftSelect: Accelerating Mobile Device Decision-Making Through Agile Recommendation
Algorithms.
10. Thompson, G. C. (2022). SynthAI: A Synergistic Approach to Artificial Intelligence-driven Mobile Device Recommendations.
11. Hernandez, P. F., Chang, W. (2022). FutureFlow: Anticipating User Preferences for Proactive Mobile Device Recommendations.
12. Lee, J. W. (2022). NexusAdvisor: Bridging the Gap Between User Preferences and Cutting-Edge Mobile Device Technologies.
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