Ad Selection via Media and Ad Profile Matching
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Solution Overview
Problem
Current advertisement selection for media content relies on traditional methods such as popularity and demographics, failing to effectively match advertisements with media profiles and viewer interactions, leading to suboptimal ad placement and viewer engagement.
Innovation Solution
A system that determines media profiles and advertisement profiles using metrics like laughter, outdoor, and urban environments, and selects advertisements based on these profiles, viewer interaction levels, and bidding processes, while considering playback device and medium types to optimize ad placement and engagement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional advertisement selection based on popularity and demographics is used, then advertisement placement is simple and fast, but advertisement relevance and viewer engagement are suboptimal
Solution Approach 1:
The patent segments the advertisement selection process into multiple independent components: media profile generation (segmenting media content into structured profiles with metrics), advertisement profile creation (segmenting ad inventory into contextual profiles), and matching algorithms (segmenting the selection process into relevance scoring and optimization). This segmentation enables precise measurement of advertisement relevance through detailed media metrics while managing system complexity through modular architecture.
2Productivity
If context-based advertisement selection is implemented, then viewer engagement increases, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-generating media profiles for media content and pre-creating advertisement profiles for ad inventory before the actual advertisement selection occurs. These profiles contain pre-computed metrics (laughter, outdoor, urban, etc.) that enable rapid matching during advertisement selection without requiring complex real-time analysis, thus reducing processing time while maintaining high viewer engagement through contextually relevant ads.
3Measurement precision
If detailed media metrics are collected and analyzed, then advertisement targeting precision improves, but data processing complexity increases
Solution Approach 1:
The patent transforms complex media content analysis into standardized parameter measurements (laughter metric, outdoor metric, urban metric, etc.). By converting diverse media characteristics into comparable numerical parameters with defined ranges and weights, the system achieves high targeting precision while simplifying data processing complexity through parameter normalization and standardized measurement protocols.
Data Source
AI summary
Aspects of the subject disclosure may include, for example, embodiments for determining a media profile for media content. The media profile comprises a media metric for each of a plurality of portions of the media content. Further, embodiments include determining a price for advertising associated with the media content. In addition, embodiments include identifying an advertisement profile for each of a plurality of advertisements. The advertisement profile comprises an ad metric for each of a plurality of portions of an advertisement. Also, embodiments include selecting a first advertisement associated with a first advertisement profile from the plurality of advertisements according to the media profile, the first advertisement profile, and the price for the advertising associated with the media content. Further, embodiments include providing the first advertisement to be presented with the media content at a playback device. Other embodiments are disclosed.