Personalized Search Ranking With Pairwise Alignment Filtering
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current online search engines face issues of over-inclusiveness, under-inclusiveness, and distorted rankings in search results, leading to inefficiencies in data transmission, storage, and user review time, particularly in industries like employment searching, where relevant information is often obscured or missed.
Innovation Solution
An artificial intelligence-driven system that personalizes and customizes search results and rankings using user-determined characteristics and filters, employing pair-wise alignment scoring and time duration filtering to provide highly relevant and actionable information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If keyword searching is used to retrieve documents responsive to query terms, then search results accurately correspond to search terms, but the results do not reflect user's underlying interests and goals
Solution Approach 1:
The patent segments the search process into multiple stages: initial keyword-based retrieval, followed by interactive refinement through return queries. This segmentation allows the system to first capture explicit search term correspondence, then progressively uncover implicit user interests through structured interaction, resolving the contradiction between term accuracy and user intent alignment
Solution Approach 2:
The system performs preliminary action by proactively generating return queries based on initial search results and user profiles before the user completes their search. This preliminary analysis of user interests and goals allows the system to pre-filter and personalize results, preventing information loss while maintaining term correspondence
2Quantity of substance
If a large number of search results are returned to ensure comprehensive coverage, then more relevant information may be included, but the user cannot review all results in a reasonable period of time
Solution Approach 1:
The system applies partial action by returning a focused subset of highly relevant results through personalized filtering and ranking, rather than exhaustive results. The interactive return query mechanism allows progressive refinement, delivering sufficient information coverage without overwhelming the user, thus reducing review time while maintaining comprehensive coverage of relevant information
Solution Approach 2:
The system dynamically changes parameters such as result ranking criteria, filtering thresholds, and personalization weights based on user feedback and interaction patterns. This adaptive parameter adjustment optimizes the balance between result quantity and review efficiency, ensuring users receive appropriately sized result sets tailored to their specific needs and time constraints
3Ease of operation
If search results are ranked according to provider criteria such as link count or bidding, then results are organized systematically, but the rankings are distorted and over-inclusive
Solution Approach 1:
The system incorporates feedback mechanisms where user interactions with search results (clicks, selections, return queries) continuously inform and adjust ranking algorithms. This feedback loop replaces static provider-based ranking criteria with dynamic user-centered ranking, maintaining systematic organization while eliminating distortion from link counting or bidding, thereby improving ranking accuracy
Solution Approach 2:
The patent transforms static ranking criteria into dynamic, adaptive ranking that responds to user behavior and preferences in real-time. Ranking parameters adjust based on user feedback, session context, and personalization data, ensuring results remain systematically organized while accurately reflecting user relevance rather than provider metrics
4Measurement precision
If keyword searching is used to filter results, then specific terms can be targeted, but relevant information that does not utilize the particular keyword is missed
Solution Approach 1:
The system achieves universality by implementing multiple search modalities: keyword-based retrieval for explicit term matching, and return query-based discovery for implicit interest identification. This multi-functional approach ensures both specific keyword targeting and comprehensive relevant information coverage, including content that may not contain exact search terms but addresses user needs
Data Source
AI summary
Various embodiments of a computer server system and method provide for personalization and customizable filtering of network search results and search result rankings. A representative server system includes: 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 configured to select, using the query, 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; to time duration filter the plurality of respondent and co-respondent combinations; 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.