Media Measurement System Using Exogenous Data for Identification
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Solution Overview
Problem
Traditional media measurement systems are inadequate for tracking media consumption patterns across multiple channels and are limited in accurately measuring audience engagement with advertisements, as they rely on channel identification and code-based content recognition, which is inefficient and prone to errors, especially in noisy environments.
Innovation Solution
A media measurement system that enhances content recognition by analyzing information exogenous to the media sample, utilizing audience data and media player log data to improve identification accuracy and efficiency, and adjusts sample construction and selection parameters based on identification results, while also deducing play-altering activities from content offset values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If continuous searching against a large database of media content is performed using content recognition technologies, then content identification capability is improved, but computational intensity increases
Solution Approach 1:
The system performs preliminary actions by extracting and analyzing exogenous information (audience data, media player log data, sample sequence data) before conducting content recognition. This preliminary analysis filters and prepares the search space, allowing the subsequent content recognition to be more targeted and less computationally intensive while maintaining high accuracy.
Solution Approach 2:
The system introduces intermediary data structures and processing layers that mediate between the raw media samples and the content recognition database. By using exogenous information as intermediaries to guide the recognition process, the system reduces the computational burden of searching the entire database while improving identification accuracy.
2Reliability
If content recognition systems operate in high-noise environments, then robustness is improved, but erroneous results increase
Solution Approach 1:
The system implements feedback mechanisms where exogenous information (audience data, play-altering activity detection) is continuously used to validate and correct content recognition results. When erroneous identifications are detected through feedback from exogenous data sources, the system can correct them, maintaining high accuracy even in noisy environments.
Solution Approach 2:
The system changes parameters by adjusting the weight and type of information used in recognition based on environmental conditions. In high-noise environments, the system increases reliance on exogenous information and adjusts the threshold and weighting parameters of content recognition algorithms to better handle noisy inputs while maintaining accuracy.
3Ease of operation
If channel-centric media measurement is used, then traditional monitoring is simplified, but media consumption tracking across multiple channels becomes inadequate
Solution Approach 1:
The system achieves universality by designing a single integrated platform that can track media consumption across multiple channels and devices. By using exogenous information from various sources (audience data, media player logs, sample sequence data), the system provides unified measurement capabilities that work across television, radio, digital media, and other platforms without requiring separate channel-centric systems.
4Ease of manufacture
If code-based content recognition is used, then implementation is simplified, but tracking capability is limited to encoded content only
Solution Approach 1:
The system replaces the mechanical/code-based recognition approach with an information-processing approach that uses exogenous data and content recognition algorithms. This substitution allows the system to track unencoded content by analyzing audio characteristics, sample sequences, and exogenous information sources, thereby expanding content tracking coverage while maintaining implementation feasibility through software-based processing.
Data Source
AI summary
Media monitoring and measurement systems and methods are disclosed. Some embodiments of the present invention provide a media measurement system and method that utilizes audience data to enhance content identifications. Some embodiments analyze media player log data to enhance content identification. Other embodiments of the present invention analyze sample sequence data to enhance content identifications. Other embodiments analyze sequence data to enhance content identification and/or to establish channel identification. Yet other embodiments provide a system and method in which sample construction and selection parameters are adjusted based upon identification results. Yet other embodiments provide a method in which play-altering activity of an audience member is deduced from content offset values of identifications corresponding to captured samples. Yet other embodiments provide a monitoring and measurement system in which a media monitoring device is adapted to receive a wireless or non-wireless audio signal from a media player, the audio signal also being received wirelessly by headphones of a user of the monitoring device.