Taxonomy-Based Data Organization for Audience Discovery
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Solution Overview
Problem
Content publishers face difficulties in discovering relevant third-party audience data sets due to their non-uniform nature, leading to missed opportunities for both data providers and clients in targeting specific user interests.
Innovation Solution
A content management system organizes third-party audience data sets within a predefined taxonomy, allowing for easier categorization and selection by content publishers, thereby enhancing the discoverability of relevant data sets for content campaigns.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If third party audience data sets are stored in non-uniform formats, then data providers can maintain flexibility in data collection and representation, but content publishers face difficulties in discovering and selecting relevant data sets
Solution Approach 1:
The patent introduces a standardized taxonomy structure as an intermediary layer between diverse third-party audience data sets and content publishers. This taxonomy provides uniform categorization schemas (demographics, interests, behaviors, etc.) that mediate between the flexible non-uniform data formats from different providers and the need for consistent, discoverable data organization. The taxonomy acts as a translation layer that preserves data provider flexibility while enabling publisher ease of use through standardized access patterns.
Solution Approach 2:
The patent transforms the organization parameters of audience data from provider-specific non-uniform formats into a standardized taxonomy-based structure. By changing the organizational parameters to include uniform categories (age ranges, gender, interests, device types, etc.), the system maintains the adaptability to accommodate various data sources while fundamentally altering how data is structured and accessed, thereby improving discoverability without losing data flexibility.
2Productivity
If a standardized taxonomy structure is implemented to organize third party audience data sets, then data set discoverability and selection efficiency improve, but system complexity increases
Solution Approach 1:
The patent segments the audience data taxonomy into distinct, manageable categories (demographics, interests, behaviors, device characteristics, geographic information). Each category contains specific attributes that can be independently configured and populated. This segmentation allows the complex taxonomy system to be broken down into modular components that can be processed, searched, and managed separately, thereby improving selection efficiency while making the overall system complexity more tractable through structured organization.
3Measurement precision
If comprehensive audience data sets are collected and organized, then targeting precision for content campaigns improves, but data processing and matching time increases
Solution Approach 1:
The patent applies preliminary action by pre-organizing third-party audience data into the standardized taxonomy structure before actual content campaign matching occurs. Data providers submit their audience data sets to be categorized and structured according to the taxonomy schemas in advance. This preliminary organization creates ready-to-use, uniformly structured data that can be quickly queried and matched during campaign execution, thereby maintaining high targeting precision while reducing real-time processing time.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for processing non-uniform datasets. In one aspect, a method includes receiving multiple different datasets that have non-uniform labeling conventions and that are not organized in a hierarchical structure, organizing the multiple different datasets that are not organized in a hierarchical structure, into a predefined hierarchical taxonomy, including, analyzing text included in the dataset, assigning the dataset to one or more categories within the predefined hierarchical taxonomy based on the analysis of the textual content and one or more other characteristics of the dataset including a number of identification entries included in the dataset, selecting content for display within the content interface at the user device using one or more of the multiple different datasets that were organized into the predefined hierarchical taxonomy, providing, through the user frontend, the selected content for presentation at the user device.