Client-Side Service Data Aggregation for Risk Analysis
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Solution Overview
Problem
Existing risk identification methods for service data are inefficient due to the need for multiple calls between systems, leading to prolonged processing times and increased resource consumption, especially when dealing with large amounts of time streams of service data.
Innovation Solution
The method involves aggregating service data on the client-side before transmission to the server, allowing for reduced network and resource usage by performing processing operations on the server-side, which has greater capabilities, and using an iterative decay function to calculate risk scores, thereby minimizing storage and computing overhead on the client.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple calls are made between client and server to retrieve service data, then complete service data can be obtained, but transmission time and network resource consumption increase
Solution Approach 1:
The patent applies preliminary action by aggregating service data on the client side before transmission to the server. This pre-processing step consolidates multiple data requests into a single aggregated dataset, eliminating the need for multiple round-trip calls between client and server, thus reducing transmission time while maintaining data completeness
Solution Approach 2:
The patent merges multiple service data streams into a single aggregated dataset on the client side. By combining multiple data requests and their responses into one consolidated transmission, the system reduces the number of network calls from multiple sequential operations to a single batch operation, thereby reducing overall transmission time
2Reliability
If multiple calls are made between client and server to retrieve service data, then complete service data can be obtained, but network resource consumption increases
Solution Approach 1:
The patent applies preliminary action by aggregating service data on the client side before transmission to the server. This pre-processing step consolidates multiple data requests into a single aggregated dataset, eliminating the need for multiple round-trip calls between client and server, thus reducing transmission time while maintaining data completeness
Solution Approach 2:
The patent merges multiple service data streams into a single aggregated dataset on the client side. By combining multiple data requests and their responses into one consolidated transmission, the system reduces the number of network calls from multiple sequential operations to a single batch operation, thereby reducing overall transmission time
3Productivity
If processing operations are performed on the client device, then data can be processed locally, but computing resources are limited compared to server system
Solution Approach 1:
The patent applies segmentation by dividing the processing workload into two distinct segments: data aggregation and preprocessing is performed on the client device, while complex risk identification and analysis are executed on the server system. This division allows each component to operate within its capability constraints while achieving overall system efficiency
Solution Approach 2:
The patent introduces an intermediary aggregation layer on the client side that prepares data before server processing. This intermediary step consolidates raw service data into structured aggregated datasets, reducing the complexity of data that needs to be processed by the server and optimizing the use of both client and server resources
Data Source
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AI summary
Methods, systems, and computer-readable storage media for risk identification of service data using operations of determining, by a client-side computing device, a first service data corresponding to a first operation behavior associated with a user input on the client-side computing device, determining, by the client-side computing device, a first variable corresponding to the first service data, the first variable including a first eigenvalue, retrieving, by the client-side computing device, a second eigenvalue corresponding to a second operation behavior that was performed at a second time before the first operation behavior, generating, by the client-side computing device, a decay value by processing the first time and the second time a decay function, generating, by the client-side computing device, an aggregated data by processing the first variable, the second eigenvalue, and the decay value using an aggregation function, and determining, by the one or more processors, a risk associated with the first operation by processing the aggregated data using a risk identification model.