A data clustering method, device, electronic equipment and storage medium
CN116723021BActive Publication Date: 2026-06-19BEIJING KNOWNSEC INFORMATION TECHNOLOGY CO LTD
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Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- BEIJING KNOWNSEC INFORMATION TECHNOLOGY CO LTD
- Filing Date
- 2023-06-26
- Publication Date
- 2026-06-19
AI Technical Summary
Technical Problem
Existing technologies face challenges in processing network security log data, including high data cleaning costs and low clustering efficiency due to significant differences in data types and units.
Method used
By acquiring network security log data from different IP addresses, extracting feature data from different dimensions, generating visual charts and converting them into numerical matrices, and then merging and clustering them, the complex data cleaning process is avoided.
Benefits of technology
It improves the efficiency of data clustering, especially in scenarios with complex data dimensions and large differences in units, reduces the complexity of data cleaning, and enhances the clustering effect.
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Smart Images
Figure CN116723021B_ABST
Abstract
This application provides a data clustering method, apparatus, electronic device, and storage medium, relating to the field of data processing. The method includes acquiring network security log data corresponding to different IP addresses; for each IP address, extracting feature data corresponding to different dimensions from the network security log data corresponding to that IP address; generating visualization charts corresponding to different dimensions of that IP address based on the feature data corresponding to those different dimensions; converting each visualization chart into a numerical matrix; merging the numerical matrices corresponding to the same IP address to obtain a feature matrix corresponding to each IP address; and clustering each feature matrix. By using the visualization images of feature data from different dimensions in the network security log data as the basis for clustering, complex cleaning processes for data of different data types and different data units in the network security log data are eliminated, improving the efficiency of data clustering.
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