Asset Targeting Using Household Classifiers in Limited Resource Environments
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Solution Overview
Problem
Existing asset targeting systems in broadcast networks face challenges in environments with limited resources, such as satellite television networks, where real-time voting and reporting processes are not feasible due to lack of return channels, and resource constraints at set-top boxes (STBs), necessitating reduced functionality and redistribution of functionality across the network.
Innovation Solution
A system and method that generates household classifiers based on correlated household and network usage information, allowing user equipment devices to select appropriate assets for delivery, even in resource-limited environments, by processing household information from repositories and network usage data to provide targeted asset options.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time voting and reporting processes are implemented at user equipment devices, then asset targeting accuracy is improved, but device complexity and resource requirements increase
Solution Approach 1:
The patent extracts the voting and reporting functionality from the STB and relocates it to the network platform. The STB only retains the ability to receive and display assets, while the complex processing of household information, network usage data, and real-time voting occurs at the network platform, thereby reducing STB resource requirements while maintaining targeting accuracy.
Solution Approach 2:
The network platform serves as an intermediary between the STB and the asset selection process. It receives household information and network usage data, processes this information to generate classifiers, and provides targeted asset options to the STB, eliminating the need for complex local processing at the STB.
2Productivity
If real-time voting processes are implemented, then asset targeting effectiveness is improved, but loss of time in resource-constrained environments increases
Solution Approach 1:
The system performs preliminary action by pre-processing household information and network usage data to generate household classifiers before the actual asset selection. This pre-computation of classification parameters allows for rapid asset selection without time-consuming real-time analysis during the voting process.
Solution Approach 2:
The patent creates a simplified copy of the voting process that operates asynchronously. Instead of requiring real-time interaction, the system uses pre-generated household classifiers as representations of user preferences, allowing asset selection to occur without simultaneous user input while maintaining targeting effectiveness.
3Adaptability or versatility
If individualized classifiers are provided to each household, then adaptability of asset targeting is improved, but device complexity increases
Solution Approach 1:
The patent extracts the classifier generation and processing functionality from the STB and relocates it to the network platform. The STB simply receives and applies the pre-generated household classifiers to select assets, while the complex analysis of household information and network usage patterns occurs at the network platform, maintaining adaptability while reducing device complexity.
Solution Approach 2:
The network platform provides universal classifier generation service that serves multiple households simultaneously. By centralizing the complex processing at the network level, the system achieves multi-functionality where a single platform handles classification for numerous households without requiring each STB to have complex processing capabilities.
4Measurement precision
If return channels for communication from user equipment are used, then measurement precision of user information is improved, but loss of energy in limited resource environments increases
Solution Approach 1:
The system employs periodic action by using event-triggered communication where STBs transmit usage information to the network platform only at specific intervals or when significant changes occur, rather than continuously. This periodic reporting maintains measurement precision of user information while significantly reducing energy consumption compared to continuous communication.
Solution Approach 2:
The STB performs self-service by locally processing and filtering network usage data before transmission to the network platform. By pre-processing and prioritizing which data to transmit, the STB reduces the amount of data communication, thereby maintaining information accuracy while minimizing energy consumption in resource-constrained environments.
Data Source
AI summary
The present invention provides targeted asset system implementations in contexts where there is limited or no ability to use a real-time return channel for communications from user equipment devices (e.g., STB) to the network. In one arrangement, a household classifier is generated and delivered to user equipment devices. The household classifiers are generated based on third party data and/or network usage information associated with the household. The system and method allow for generating highly accurate household classifications that may be forwarded to individual households where the user equipment device may implant the classifiers to select appropriate assets for delivery to the household.