Dynamic Advertisement Selection Based on Contextual Relevance
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Solution Overview
Problem
Current advertisement systems fail to provide relevant and effective advertisements in dwelling spaces due to their inability to adapt to changing circumstances and user demographics, leading to low impact and cost inefficiency.
Innovation Solution
An advertisement distribution system that calculates a base fee and additional fee for each advertisement based on predefined criteria, determining its appropriateness for the indoor space, and selects advertisements for display based on the sum of these fees, ensuring relevance and matching properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If advertisements are selected based solely on bid price and CTR, then advertiser revenue is maximized, but advertisement relevance to current circumstances and user demographics deteriorates
Solution Approach 1:
The patent transforms the advertisement selection criteria from static parameters (bid price, CTR) to dynamic parameters that include temporal context, user demographics, and environmental factors. The selection formula incorporates multiple variable parameters: advertisement relevance score, user profile matching degree, temporal context factors, and demographic alignment metrics, allowing the system to adapt to changing circumstances while maintaining revenue optimization.
Solution Approach 2:
The system implements dynamic advertisement selection by continuously updating the relevance assessment based on real-time user behavior, changing environmental contexts, and evolving demographic patterns. The advertisement selection is no longer fixed but dynamically adjusts to current circumstances, user state, and contextual factors, making the system responsive and adaptive rather than static.
2Productivity
If the same advertisement is repeatedly provided to a user, then advertisement delivery efficiency is improved, but user satisfaction and rationality of advertisement provision deteriorates
Solution Approach 1:
The patent implements periodic re-assessment of advertisement relevance before repeated delivery. Instead of continuously showing the same advertisement, the system periodically evaluates whether the advertisement remains relevant to the user's current state, circumstances, and demographics. This periodic validation ensures that repeated advertisements maintain user satisfaction while preserving delivery efficiency for genuinely relevant content.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor user responses to advertisements and use this information to adjust future advertisement selection. By analyzing user behavior patterns, engagement metrics, and satisfaction indicators, the system provides feedback loops that prevent repetitive advertisement delivery when user satisfaction decreases, while maintaining efficient delivery when positive feedback is received.
3Adaptability or versatility
If advertisement selection is based on comprehensive criteria including circumstances and demographics, then advertisement relevance is improved, but system complexity increases
Solution Approach 1:
The patent segments the complex advertisement selection process into distinct modular components: user profile analysis module, contextual environment assessment module, advertisement relevance scoring module, and selection optimization module. Each module handles a specific aspect of the evaluation, processing independent data streams and producing intermediate results that are combined in a structured manner, thereby managing complexity through functional segmentation.
Solution Approach 2:
The system introduces an intermediary advertisement selection module that acts as a mediator between raw data inputs (user demographics, contextual information, advertisement content) and the final selection output. This intermediary layer processes and integrates multiple data sources, applies the selection formula, and produces the final advertisement choice, simplifying the overall system architecture by centralizing the complex decision-making logic in a dedicated intermediary component.
Data Source
AI summary
Provided is a method of providing an advertisement in an indoor space using a system including a processor and a memory storing information about a content of each of advertisements including a first advertisement. The method includes: (a) calculating a base fee of the first advertisement from a content of the first advertisement stored in the memory based on a first criterion determined in advance based on a viewer's impression of each advertisement; (b) calculating an additional fee of the first advertisement from the content of the first advertisement based on a second criterion determined in advance to determine whether to be an advertisement improper to the system; (c) selecting an advertisement to be provided from among the plurality of advertisements based on a sum of the base fee calculated and the additional fee calculated; and (d) outputting an instruction to provide, to the indoor space, the advertisement selected.