Titlebook: Advances in Artificial Intelligence and Machine Learning in Big Data Processing; First International R. Geetha,Nhu-Ngoc Dao,Saeed Khalid C

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Vehicle Insurance Claim Predictioning more common, and in insurance companies, the amount of claim data is rising. Therefore, during the claim re-view procedure, it could be challenging to ascertain the insured claim status. Consequently, the target of the review was to foster an AI model that sorts and conjectures the recurrence of

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Ensemble Learning Models for Detecting Spam Over Social Networks Using RFEs of users utilizing them on a daily basis. While they have emerged as a means of disseminating information, they have also quickly transformed into a conduit for spreading false information, rumors, unsolicited messages, promotional content, fabricated news, and other undesirable content. Both spam

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Online Network Intrusion Detection System for IOT Structure Using Machine Learning Techniques this study, we propose a novel Machine Learning-based Online Network Intrusion Detection System (NIDS) specifically tailored for IoT architecture. Our approach harnesses the potential of advanced Machine Learning algorithms to overcome the limitations of conventional NIDS solutions. The primary obj

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An Analysis of Machine Learning Tools and Algorithmsilarity measures falls into two main areas of machine learning namely supervised learning and Unsupervised Learning. Machine learning algorithms deals with the data and datasets. The main difference between the supervised and unsupervised learning is to predict the labelled and unlabeled data.

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Ensemble Learning-Based Android Malware Detectionger current lines using unexpectedly cutting-edge detection evasion strategies. Options for timely 0-day detection are necessary as standard signature-based approaches become less effective in detecting unknown threats. This study contributes a strategy based on ensemble learning for detecting malic

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Conference proceedings 2025om 183 submissions. They were organized in the following topical sections: ..Part I- artificial intelligence and data analytics; deep learning...Part II- artificial intelligence and data analytics; machine learning..

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1865-0929 elected from 183 submissions. They were organized in the following topical sections: ..Part I- artificial intelligence and data analytics; deep learning...Part II- artificial intelligence and data analytics; machine learning..978-3-031-73067-2978-3-031-73068-9Series ISSN 1865-0929 Series E-ISSN 1865-0937

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,Radioaktivität und Kernreaktionen,f computer vision technology and object detection methods combined with the ability of OpenCV to analyze and interpret hand gestures holds an opportunity to revolutionize interaction for hard-of-hearing people, increasing their access to information, education, and work possibilities.