Personalized Search Ranking via User Profile Feedback
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Solution Overview
Problem
Current online search engines using keyword-based searching face issues of over-inclusiveness, under-inclusiveness, and distorted search result rankings, leading to inefficiencies in retrieving relevant information, increased data transmission, and high system loads, particularly in industries like employment searching where this results in wasted time and resources.
Innovation Solution
An artificial intelligence-driven system that personalizes search results and rankings by using user-determined characteristics and customizable filters, automating the searching process to provide relevant information without overwhelming users with irrelevant data, and incorporating time sensitivity with push notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If keyword-based searching is used to retrieve documents responsive to search terms, then search results accurately correspond to search keywords, but the search results do not reflect the user's underlying interests and goals
Solution Approach 1:
The system employs feedback mechanisms by analyzing user interactions with search results (clicks, dwell time, scrolling behavior) to continuously refine and update user profiles. This feedback loop enables the search engine to adapt to evolving user interests and goals, transforming static keyword matching into dynamic, personalized result generation that reflects real-time user needs.
Solution Approach 2:
The invention changes the fundamental parameters of search result generation from keyword-based to profile-based. By transitioning from matching documents against fixed keywords to matching documents against dynamically generated user profiles, the system achieves both accurate keyword correspondence and personalized relevance, resolving the contradiction between precision and adaptability.
2Reliability
If keyword searching is used to retrieve search results, then relevant documents can be found, but too many search results are returned that the user cannot review all of the results in a reasonable period of time
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing detailed user profiles that capture interests, goals, and preferences before the actual search occurs. These pre-generated profiles enable the search engine to immediately filter and rank results according to individual user criteria, eliminating the need for users to manually sift through large result sets and significantly reducing review time while maintaining high relevance.
Solution Approach 2:
The invention extracts and removes irrelevant results from the search output by using user profiles as filtering criteria. The system identifies and extracts only the subset of results that match both keyword queries and user-specific preferences, presenting a condensed, highly relevant list that users can review efficiently without time loss.
3Ease of operation
If search providers return results ranked according to criteria applied by the search provider, then search results can be organized, but the ranked search results are distorted by over-inclusion of irrelevant websites and distortion of rankings
Solution Approach 1:
The system applies local quality by customizing search result rankings according to each user's unique profile and preferences rather than using a uniform ranking algorithm. Each user receives personalized rankings that prioritize relevant results based on their specific interests, goals, and historical behavior, eliminating the distortion of generic provider-based rankings while maintaining organized presentation.
4Productivity
If keyword searching is used, then search results can be retrieved, but the increased amount of data transmitted to the user obscures or buries the relevant data sought by the user
Solution Approach 1:
The invention segments the search results into highly relevant portions by using user profiles to filter and prioritize. Instead of transmitting all retrieved data, the system segments and transmits only the curated subset that matches user criteria, making relevant information immediately visible and accessible without being buried in irrelevant data, thus maintaining productivity while preventing information loss.
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.