Streaming Service Source Deduction for Non-Linear Media Exposure
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Solution Overview
Problem
Existing media-monitoring systems face challenges in accurately determining the source of non-linear content presented by media-presentation devices, particularly when the last mile of media delivery does not traverse a local area network, making it difficult to identify which streaming-media service provided the content.
Innovation Solution
A computing system deduces the source of non-linear content by finding an intersection between a set of streaming-media services available to the panelist site and a set of services known to offer the identified content, utilizing subscription data and additional factors like commercial breaks to enhance accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If media-monitoring systems use traditional monitoring methods to track linear content, then they can accurately identify content source, but they fail to accurately determine the source of non-linear content when the last mile of media delivery does not traverse a local area network
Solution Approach 1:
The patent segments the content identification process into two distinct paths: one for linear content that traverses the local area network (using traditional watermarking and signature matching) and another for non-linear content that does not traverse the local area network (using intersection analysis of available services and offered content). This segmentation allows the system to apply appropriate methods for each content type, resolving the contradiction between maintaining accuracy for linear content while adapting to non-linear content delivery.
Solution Approach 2:
The patent performs preliminary actions by maintaining a database of panelist site subscriptions to streaming-media services and pre-collecting information about which services offer which content. Before attempting to identify the source of non-linear content, the system has already gathered subscription data and content catalogs, enabling it to quickly perform intersection analysis when content is presented, thus achieving accurate source identification for non-linear content without real-time network traversal.
2Measurement precision
If the system monitors all packet data flow on the local area network to identify content source, then it can accurately trace non-linear content, but it cannot identify content when the last mile of delivery does not traverse the local area network
Solution Approach 1:
The patent introduces an intermediary approach by using the panelist site's subscription information and service catalogs as mediators to infer content source. Instead of directly monitoring the actual content delivery path (which may not traverse the local area network), the system uses subscription data and content catalogs as intermediate information to perform intersection analysis, thereby recovering content source information that would otherwise be lost when the last mile does not traverse the local area network.
3Measurement precision
If the system uses intersection analysis of subscription data and content catalogs to identify non-linear content source, then it can resolve ambiguity in content sourcing, but it requires additional data collection and processing
Solution Approach 1:
The patent applies preliminary action by pre-collecting and storing subscription data and content catalogs in databases before they are needed for content identification. This advance preparation means that when non-linear content is presented and source identification is required, the system can perform intersection analysis using pre-gathered data without needing to collect information in real-time, thus reducing the processing complexity at the moment of identification while maintaining high accuracy.
Data Source
AI summary
A method and system for media-exposure monitoring. An example method includes a computing system receiving digital query signature data representing a media content item presented at a panelist site. Further, the method includes the computing system identifying the media content item, with the identifying being based on matching of the received digital query signature data with reference signature data. Still further, the method includes the computing system determining a streaming-media service that streamed the identified media content item to the panelist site for presentation, with the determining of the streaming-media service including finding an intersection of (i) a first set of one or more streaming-media services known to offer streaming of the media content item and (ii) a second set of one or more streaming-media services to which the panelist site subscribes.