Research on Multimedia Information Processing System based on Data Mining Technology

This scholarly paper presents the main findings of an in-depth exploration of multimedia data mining, focusing on the extraction and organization of metadata from expansive multimedia datasets. The study employs a multidimensional analysis approach using multimedia data cubes, which provide a comprehensive representation of the data. The paper emphasizes the importance of result presentation and advocates for the use of visualization techniques to effectively convey mining outcomes. Various techniques in multimedia mining are examined, including text data mining for extracting meaningful patterns from multimedia text data, and image data mining for discovering significant patterns from multimedia image data. Video data mining is also explored, involving the automatic extraction of content, structural features, and semantic information from video objects. The methodologies employed in video mining encompass statistics, classification, clustering, association, and trend analysis. The paper concludes by discussing system design, aiming to optimize the multimedia information processing system based on data mining technology. This comprehensive approach ensures the seamless integration of various data mining techniques, enhancing the efficiency and effectiveness of multimedia data analysis.