Russian Federation
The article discusses the application of a methodology for processing and intelligent grouping of multimodal data related to destructive behavior on the Internet. Particular attention is paid to the automated processing of heterogeneous data, including text data, photos and videos, followed by their classification and grouping based on machine learning methods. The purpose of this study is to develop a methodology for processing and intelligent grouping to identify destructive behavior. The methodology includes the stages of preliminary data cleaning and normalization, extracting key features using natural language processing and computer vision. A feature of the approach is the integrated use of methods for processing multimodal data and their grouping by the overall context, and not just by individual features. The result of the processing is a structured presentation of data for further analysis and decision making. The methodology has been tested on real data from social networks. The use of this approach allows you to adapt the processing of large volumes of heterogeneous data from the Internet and improve the quality of their grouping for monitoring tasks and decision-making recommendations.
intelligent grouping, data processing, multimodal data, destructive behavior, social networks, NLP, CV
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