Implicit Analytic Data Upload via Dependency Rules
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Solution Overview
Problem
Current systems incur overheads such as increased device cost, processing requirements, and reduced battery life due to continuous uploads of analytic data, and fail to efficiently upload implicit event data based on explicit user activity, leading to incorrect responses and unnecessary data transmission.
Innovation Solution
A method and apparatus that upload implicit analytic data based on explicit activity by storing dependency rules, evaluating these rules to identify relevant implicit event data, and triggering the upload of this data in conjunction with explicit event data, thereby reducing unnecessary data transmission and improving response times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous or real-time uploads of analytic data are performed, then data analysis and user profiling accuracy is improved, but device cost, processing requirements, and battery life are adversely impacted
Solution Approach 1:
The patent implements periodic batched uploads of analytic data instead of continuous real-time transmission. The system collects analytic data locally and transmits it in periodic batches, reducing the frequency of network communications and associated energy consumption while maintaining data analysis accuracy.
Solution Approach 2:
The patent extracts and transmits only the necessary analytic data elements required for accurate user profiling and analysis, rather than transmitting all collected data continuously. This selective data transmission reduces the volume of data sent over the network and the energy required for transmission.
2Measurement precision
If continuous or real-time uploads of analytic data are performed, then data analysis and user profiling accuracy is improved, but device cost, processing requirements, and battery life are adversely impacted
Solution Approach 1:
The patent segments the analytic data transmission process into discrete batched updates rather than continuous streaming. This segmentation allows the system to process and transmit data in manageable chunks, reducing the instantaneous processing load and computational complexity requirements.
3Use of energy by moving object
If batched updates of analytic data are performed, then device cost, processing requirements, and battery life are improved, but user experience and response time are degraded
Solution Approach 1:
The patent performs preliminary local processing and buffering of analytic data on the device before transmission. Data is collected and prepared in advance during idle periods, so when batched uploads occur, the processing time is minimized and response time to the server is improved without requiring continuous active processing.
4Loss of information
If all implicit event data is uploaded continuously, then complete data context is provided, but network bandwidth and data transmission overhead are increased
Solution Approach 1:
The patent extracts and transmits only the relevant implicit event data that is necessary for accurate analysis and user profiling, filtering out redundant or less important data elements. This selective extraction maintains data context completeness while significantly reducing the volume of data transmitted over the network.
Solution Approach 2:
The patent implements partial uploading of implicit event data by transmitting only the subset of data that is most relevant to current analysis needs, rather than uploading all collected data. This partial action approach provides sufficient context for accurate profiling while minimizing network bandwidth consumption.
Data Source
AI summary
A method (300) and apparatus (110, 150) collect and upload implicit analytic data. The method can include storing (320) dependency rules corresponding explicit events to implicit events. The method can include collecting (330) and storing (340) implicit event data corresponding to implicit events. The method can include receiving (350) an explicit event at the device. The method can include evaluating (360) dependency rules corresponding to the explicit event. The method can include identifying (370) a relevant subset of implicit event data corresponding to the explicit event based on evaluating the dependency rules. The method can include uploading (390) the relevant subset of the implicit event data and explicit event data corresponding to the explicit event.