Consumption data report generation system based on machine learning
By building a machine learning-based consumer data report generation system, the problems of feature mining and real-time processing of large-scale heterogeneous consumer data have been solved, enabling in-depth data analysis and adaptive report generation, thereby improving the explanatory power of market fluctuations and the immediacy of decision-making.
Patent Information
- Application Number
- CN202610658235.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-13
- Publication Date
- 2026-06-26
AI Technical Summary
Existing technologies suffer from insufficient feature mining depth, limited real-time processing performance, and severe homogenization in report generation when processing large-scale heterogeneous consumer data, making it difficult to meet the immediacy requirements of dynamic decision-making.
A consumer data report generation system based on machine learning is constructed, including a multi-source heterogeneous data adaptive ingestion module, a nonlinear feature automated calculation engine, a heterogeneous behavior semantic association graph construction unit, an incremental machine learning inference center, and a multi-dimensional logical adaptive report generation platform, to achieve efficient data processing, deep feature extraction, cross-domain consumer preference analysis, and adaptive report generation.
It enables deep perception and efficient processing of massive and complex consumer data, enhances the system's explanatory power for complex market fluctuations and the logical depth of reports, meets the real-time requirements of enterprise-level applications for dynamic decision-making, and improves the efficiency of report output and practical application value.