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              <text>Application Areas, Benefits, and Research Challenges of Converging Blockchain and Machine Learning Techniques</text>
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              <text>In recent years, machine learning (ML) has become a hot topic of research and application. ML model and huge amount of data growth difficulties still follow ML development. With the lack of new data and constant training, published ML models may soon become obsolete; unscrupulous data contributors may upload incorrectly labelled data, leading to poor training results; and data leakage and abuse are all possible outcomes. These issues can be effectively addressed by using blockchain, a new and rapidly evolving technology. With the advancement of various smart devices and the field of artificial intelligence and machine learning, interdisciplinary collaboration with blockchain technology may be incredibly valuable for future investigations. Collaborative ML and blockchain convergence can be studied here, with emphasis on how these two technologies can be combined and their application areas. On the other hand, look at the existing researchs shortcomings and future enhancements.  The Author(s), under exclusive license to Springer Nature Switzerland AG. 2024.</text>
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              <text>Manimaran A.; Goundar S.; Chandramohan D.; Arulkumar N.</text>
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              <text>EAI/Springer Innovations in Communication and Computing, Vol-Part F1496, pp. 1-16.</text>
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              <text>Manimaran A., Department of Mathematics, School of Advanced Sciences, VIT-AP University, Andhra Pradesh, Amaravati, India; Goundar S., School of Science, Engineering, and Technology, RMIT University, Hanoi, Viet Nam; Chandramohan D., Department of Computer Science &amp;amp; Engineering, Thapar Institute of Engineering &amp;amp; Technology, Punjab, Patiala, India; Arulkumar N., Department of Computer Science, Christ University, Bangalore, India</text>
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