Contextual Ad Selection Using User Feature Mapping
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Solution Overview
Problem
Current online advertising methods are inefficient and intrusive, as they often display untargeted advertisements to users, leading to a negative user experience and reduced revenue for advertisers.
Innovation Solution
A contextual advertisement selection system that uses user features and web page content to select relevant advertisements by mapping user characteristics to user-relevant terms, learned through historical activity data and regression techniques, to provide targeted ads based on user interests and demographics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If untargeted advertising is used to maximize ad exposure, then the quantity of advertisements displayed increases, but user experience deteriorates and ad effectiveness decreases
Solution Approach 1:
The patent applies local quality by customizing advertisement content and placement based on individual user characteristics and preferences. Each user receives tailored ads rather than uniform advertisements, making the advertising experience locally optimized for each user segment while maintaining overall system efficiency.
Solution Approach 2:
The system dynamically changes advertisement parameters such as content, timing, and placement based on user profiles, behavior patterns, and contextual information. This allows the same advertising slot to serve different users with different ad content, maximizing relevance while maintaining high fill rates.
2Measurement precision
If contextual advertising based on web page keywords is used, then ad relevance to page content improves, but inappropriate advertisements may still be displayed regarding sensitive topics
Solution Approach 1:
The patent implements preliminary action by pre-defining exclusion rules and sensitivity filters for specific topics and contexts. Before advertisements are selected and displayed, the system checks against predefined criteria to prevent inappropriate pairings, such as avoiding airline ads near crash-related content or alcohol ads near driving content.
Solution Approach 2:
The system incorporates feedback mechanisms where user responses, complaints, and engagement patterns are continuously monitored. This feedback loop allows the system to learn from inappropriate placements and adjust its contextual matching algorithms to prevent recurrence, improving sensitivity detection over time.
3Measurement precision
If user characteristics are mapped to user-relevant terms using learning models, then advertisement targeting precision improves, but system complexity increases
Solution Approach 1:
The patent applies self-service by implementing automated learning models that continuously train on user interaction data without manual intervention. The system automatically maps user characteristics to relevant terms, updates user profiles, and refines matching algorithms autonomously, reducing the need for manual system configuration and maintenance despite the complexity of the underlying models.
Data Source
AI summary
Disclosed are apparatus and methods for facilitating contextual selection of advertisements for displaying online via a computer network. In general, user features in the form of text are provided in conjunction with web page content for contextual advertisement matching. In one embodiment, a request for an advertisement to be displayed in a current web page that has been requested by a current user is received. The current user is associated with one or more current user characteristics from a plurality of different user characteristics, and the current web page has an associated content. A mapping model and the one or more current user characteristics are used to obtain a plurality of user-relevant terms for each of the one or more current user characteristics. A combination of the content of the current web page and obtained user-relevant terms are provided for selecting an advertisement for displaying with the current web page based on such combination.