Network Activity Clustering for Device Characteristic Prediction
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Solution Overview
Problem
Current technologies fail to effectively determine computing device characteristics from network activity, which limits the ability to personalize content delivery, such as ads, based on user interests and device attributes without compromising user privacy.
Innovation Solution
A method and system that analyze network communications to identify global clusters of interest categories, create sub-clusters based on common characteristics, and assign weights to these clusters to predict the status of individual devices, allowing for targeted content placement without personally identifying end users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If network communications are analyzed to determine device characteristics, then content personalization accuracy is improved, but user privacy is compromised
Solution Approach 1:
The patent introduces global clusters as intermediary structures that aggregate network activity data from multiple users and devices. These clusters serve as mediators between raw network communications and personalization decisions, allowing the system to infer device characteristics and user interests without exposing or processing individual user identity information. The global clusters enable accurate content personalization while maintaining user anonymity by working with aggregated patterns rather than individual data points.
2Adaptability or versatility
If global clusters are created from network activity data, then content delivery personalization is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the complex task of content personalization into distinct components: global cluster creation, sub-cluster identification, characteristic determination, and content matching. This segmentation allows each component to be optimized independently and processed in a systematic pipeline, reducing overall system complexity while enabling sophisticated personalization capabilities.
Solution Approach 2:
The patent performs preliminary actions by pre-creating global clusters and sub-clusters from aggregated network activity data before actual content delivery occurs. This preprocessing step establishes ready-to-use classification structures that can be quickly applied during content personalization, reducing real-time processing complexity while maintaining high adaptability.
3Measurement precision
If sub-clusters are identified based on common characteristics, then measurement precision of device status is improved, but computational resources required increase
Solution Approach 1:
The patent applies partial action by identifying and processing only the most significant common characteristics when creating sub-clusters, rather than analyzing all possible device attributes. This selective approach maintains high measurement precision for device status prediction while reducing computational resource requirements by focusing on the most informative features.
Data Source
AI summary
Systems and methods of determining computing device characteristics from computer network activity are provided. A data processing system can obtain data identifying a global cluster that indicates an interest category and can create a sub-cluster of the global cluster based on a characteristic common to content access computing devices. A weight indicating a correlation between the characteristic common to content access computing devices and the interest category can be assigned to the sub-cluster. Responsive to a communication between a first content access computing device and a content publisher computing device, the data processing system can identify a characteristic. The data processing system can associate the first content access computing device with the sub-cluster based on the characteristic of the first content access computing device and the characteristic common to the content access computing devices, and based on the weight can determine a status of the first content access computing device.