Online Compatibility Search With Pairwise Alignment Scoring
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Solution Overview
Problem
Current online search engines provide inaccurate, over-inclusive, and under-inclusive search results, particularly in employment and social compatibility searches, due to keyword-based methods that fail to reflect user interests and goals, leading to distorted rankings and excessive data transmission, storage requirements, and increased search time.
Innovation Solution
An artificial intelligence-driven system that personalizes search results and rankings using user-determined characteristics and customizable filters, automating the selection process to provide relevant information without overwhelming users with irrelevant data, incorporating two-stage filtering and push notifications for time-sensitive information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If keyword-based search methods are used, then search results can be retrieved quickly, but the results are over-inclusive and do not reflect user interests and goals
Solution Approach 1:
The patent changes the search parameters from simple keyword matching to multi-dimensional compatibility parameters including user interests, goals, skills, and preferences. This allows the system to evaluate matches based on multiple criteria rather than just keyword presence, improving accuracy while maintaining speed through efficient parameter comparison algorithms
Solution Approach 2:
The patent replaces the mechanical keyword-matching system with an AI-driven compatibility assessment system that uses machine learning models to evaluate user-co-respondent matches. This substitution enables the system to understand semantic meaning and user intent rather than just matching literal keywords, resolving the contradiction between speed and accuracy
2Adaptability or versatility
If keyword searching is used to return comprehensive results, then more potential matches are found, but the number of results becomes excessive for users to review
Solution Approach 1:
The patent extracts only the most relevant matches from the comprehensive result set by applying compatibility thresholds and ranking algorithms. Instead of presenting all potential matches, the system extracts and presents only those above a certain compatibility threshold, significantly reducing review time while maintaining comprehensiveness for qualified matches
Solution Approach 2:
The patent segments the search results into compatibility-based categories and ranks them hierarchically. Results are divided into high-compatibility, medium-compatibility, and low-compatibility segments, with users primarily reviewing the top segment. This segmentation reduces the effective review burden while preserving access to comprehensive results if needed
3Productivity
If search results are ranked by third-party links or bidding processes, then search providers can monetize their service, but the rankings become distorted and irrelevant to user needs
Solution Approach 1:
The patent introduces an AI compatibility assessment intermediary that stands between the keyword search and the final ranking. This intermediary evaluates matches based on user interests, skills, and goals, producing an independent compatibility score that overrides third-party bidding influences. The system can still accommodate monetization through optional premium features while maintaining accurate compatibility-based rankings
Solution Approach 2:
The patent implements feedback mechanisms where user interactions with search results (clicks, selections, rejections) are used to continuously refine and adjust compatibility rankings. This feedback loop ensures that rankings remain accurate and relevant to user needs rather than being distorted by external factors, while the system adapts to individual user preferences over time
Data Source
AI summary
A computer server system and method are disclosed for personalization and customizable filtering of network search results and search result rankings, such as for Internet searching. A representative server system comprises: a network interface to receive a query from a respondent or co-respondent; at least one data storage device storing a plurality of return queries; and one or more processors adapted to access the data storage device and using the query, to select the return queries for transmission; to search the data storage device for corresponding pluralities of responses to the return queries from other co-respondents or respondents; to pair-wise score the responses and generate pair-wise alignment scores for respondent and co-respondent combinations; to sort and rank the combinations according to the alignment scores; and to output a listing of the sorted and ranked respondents or co-respondents to form the personalized network search results and search result rankings.