Abnormality Detection for Statistical Usage Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The reliability and accuracy of statistical usage data for electronic information services are compromised due to individual generation by multiple information suppliers, leading to various abnormalities, making large-scale verification impractical.
Innovation Solution
A system and method for automatically detecting abnormalities in statistical usage data by identifying data matching a standard format, detecting discrepancies, and generating notification messages for each type of abnormality, including overlapping, non-matching, and trend-based anomalies, using an abnormality detection apparatus that collects data from multiple information supplier platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If statistical usage data is collected from multiple information suppliers, then the quantity and coverage of data increases, but the reliability and accuracy deteriorate due to individual generation by each supplier
Solution Approach 1:
The patent introduces an intermediary verification system that acts as a mediator between multiple information suppliers and the final data users. This intermediary automatically verifies the statistical usage data collected from various suppliers, checking for abnormalities and ensuring data quality standards are met, thus maintaining reliability while handling large quantities of data from multiple sources.
Solution Approach 2:
The patent implements a feedback mechanism where verification results are fed back to the information suppliers. When abnormalities are detected in statistical usage data, the system notifies the relevant suppliers, allowing them to correct errors and resubmit data, thereby continuously improving data reliability through iterative verification and correction.
2Reliability
If statistical usage data is verified manually, then the reliability increases, but the time consumption and cost increase significantly
Solution Approach 1:
The patent replaces the manual mechanical verification process with an automated computer-based verification system. The system uses algorithms and software to automatically check statistical usage data for abnormalities, eliminating the need for manual verification while maintaining or improving reliability, thus significantly reducing time consumption and costs.
Solution Approach 2:
The verification system is designed to autonomously perform data validation without human intervention. It automatically detects abnormalities, identifies problematic data patterns, and generates verification reports, enabling the system to serve itself in the verification process and eliminating time-consuming manual labor.
3Measurement precision
If all statistical usage data is subjected to abnormality detection, then the accuracy improves, but the processing complexity and resource requirements increase
Solution Approach 1:
The patent segments the verification process into distinct modules: data collection, format validation, abnormality detection, and result reporting. Each module handles specific aspects of verification independently, reducing overall system complexity while maintaining comprehensive detection accuracy. The segmented approach allows parallel processing and easier maintenance.
Solution Approach 2:
The verification system applies different verification strategies and thresholds to different types of statistical usage data based on their specific characteristics. Rather than using a uniform verification approach for all data, the system tailors its detection methods to local data properties, improving accuracy while optimizing resource allocation and reducing unnecessary processing complexity.
Data Source
AI summary
The present invention discloses a system for automatically detecting abnormalities in statistical data on usage, to a method for same, and to an apparatus applied to same. Namely, the present invention can increase the reliability and accuracy of statistical data on usage by: collecting statistical data on usage, the data relating to the usage of electronic information from a plurality of information-providing platform apparatuses each issuing separate electronic information; and, from among the collected statistical data on usage, determining, as data to be subjected to abnormality detection, only the statistical data on usage that corresponds to a reference data format, and detecting abnormalities for each type from the statistical data on usage determined as the data to be subjected to abnormality detection.