This article highlights the role of data collection and processing in vehicle matching systems, indicating the significance of machine learning in personalization.
This article discusses the key aspects of data collection needed to develop an intelligent vehicle matching system. Data sources, their structure, methods of processing and storage, as well as problems arising during their collection and integration are considered. Special attention is paid to the use of machine learning and recommendation algorithms to analyze user preferences and create personalized offers.
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Guk et al. (2025) studied this question.
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