AR Advertisement System with Context-Based Matching
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Solution Overview
Problem
Current advertising methods often fail to deliver targeted advertisements effectively, wasting resources by not reaching the right audience at the right time, as they lack context-based and content-matched approaches.
Innovation Solution
A system and method for providing context-based, personalized advertisements using real-time augmented reality enhancement, which involves extracting real-life objects from their environment and integrating them with virtual environments, incorporating user preference and context information to determine and embed advertisement elements dynamically.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional advertising methods are used to reach broad audiences, then advertisement coverage is improved, but resource waste increases due to lack of targeted delivery
Solution Approach 1:
The patent segments the advertising delivery process by dividing the audience into specific target groups based on user profile data, context information, and content matching criteria. This allows advertisements to be segmented and delivered only to relevant users rather than broadcast to all users, thereby maintaining coverage for target audiences while reducing resource waste on non-targeted delivery.
Solution Approach 2:
The system performs preliminary actions by pre-processing user profile information, context data, and advertisement content before actual delivery. The comprehensive content matching mechanism pre-evaluates compatibility between advertisements and user contexts, preparing targeted advertisement lists in advance. This preliminary filtering ensures that only relevant advertisements are delivered, improving coverage for matched users while eliminating waste from irrelevant deliveries.
2Speed
If advertisements are delivered without context-based matching, then delivery speed is improved, but advertising effectiveness deteriorates due to lack of relevance
Solution Approach 1:
The system performs preliminary content matching and context analysis before advertisement delivery. User profiles, context information, and advertisement criteria are pre-processed and matched offline or in advance. This preliminary action ensures that when advertisements are delivered, they are already optimized for relevance, maintaining high delivery speed while ensuring effectiveness through pre-established context-based matching.
Solution Approach 2:
The comprehensive content matching mechanism incorporates feedback loops that continuously refine advertisement delivery based on user interactions, context changes, and effectiveness metrics. User responses and engagement data feed back into the matching algorithm, improving the precision of context-based matching over time. This feedback ensures that delivery speed does not compromise effectiveness, as the system learns and adapts to deliver more relevant advertisements faster.
3Measurement precision
If comprehensive content matching with multiple factors is implemented, then advertising precision is improved, but system complexity increases
Solution Approach 1:
The complex content matching system is segmented into modular components: user profile analysis module, context information processing module, advertisement content evaluation module, and matching decision module. Each module handles specific factors independently (user preferences, context data, content criteria), processing them separately before integration. This segmentation maintains high targeting precision by thoroughly evaluating multiple factors while reducing system complexity through modular architecture and independent processing streams.
4Reliability
If real-time augmented reality enhancement is added to advertisements, then user engagement is improved, but processing time increases
Solution Approach 1:
The system performs preliminary preparation for augmented reality enhancement by pre-processing advertisement content, pre-rendering AR elements, and pre-establishing integration templates before actual advertisement delivery. User context and advertisement content are pre-matched and prepared for AR integration. This preliminary action ensures that real-time AR enhancement can be applied quickly during delivery, improving user engagement through immersive experiences while minimizing processing time through advance preparation.
Data Source
AI summary
Disclosed herein are methods and systems for intelligent and personalized advertisement in an augmented reality environment. In particular, a plurality of integrated images of an extracted real-life object in a virtual environment is provided at a server to a user. The plurality of integrated images comprises one or more advertisement elements that are determined using a comprehensive content matching mechanism. The comprehensive content matching mechanism is based on a plurality of factors intelligently determined and personalized comprising advertisement content, user preference information, and context information.