Physiologically Informed Network Search Indexing
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Solution Overview
Problem
Current internet search algorithms provide sub-optimal search results due to general ranking criteria that do not account for individual user physiological data, leading to inefficient search outcomes.
Innovation Solution
A system and method for physiologically informed network searching, which involves a computing device that receives biological data from users, classifies it using an index classifier generated by clustering user physiological data records into cohort labels, and generates a physiologically linked web index to provide tailored search results based on user physiological similarities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If general ranking criteria are used for search results, then search algorithm simplicity is maintained, but search accuracy for individual users deteriorates
Solution Approach 1:
The patent segments users into distinct cohorts based on physiological data characteristics. Instead of treating all users uniformly with general ranking criteria, the system divides the user population into segments (cohorts) that share similar physiological traits, enabling tailored search results for each segment while maintaining overall system simplicity.
Solution Approach 2:
The patent changes the parameters used for search ranking from general criteria to physiology-based parameters. By incorporating biological extractions and physiological data as new parameters for cohort classification and search indexing, the system improves search accuracy without significantly increasing algorithmic complexity.
2Adaptability or versatility
If physiological data is collected and processed for each user, then search personalization improves, but system complexity increases
Solution Approach 1:
The patent merges individual physiological data from multiple users to create cohort-level patterns. By combining and aggregating physiological extractions across user populations, the system identifies common characteristics that define cohorts, reducing the need to process and store detailed individual data while achieving effective personalization.
Solution Approach 2:
The patent creates cohort profiles that represent groups of users with similar physiological characteristics. Instead of maintaining separate processing paths for each individual, the system creates representative copies (cohort profiles) that capture the essential physiological patterns, enabling personalized search results with reduced system complexity.
3Reliability
If cohort classification is performed using classification algorithms, then search result relevance improves, but processing time increases
Solution Approach 1:
The patent performs cohort classification and creates physiologically-linked web indices in advance, before actual search queries are submitted. By pre-processing physiological data and organizing web content according to cohort characteristics ahead of time, the system eliminates the need for real-time classification during user searches, significantly reducing processing time while maintaining high relevance.
Data Source
AI summary
In an aspect, a system for physiologically informed network searching, includes a computing device designed and configured to receive a biological extraction from a user, input the biological extraction to an index classifier, the index classifier configured to input biological extractions and output web search indices, wherein the classifier is generated by executing a classification algorithm clustering a plurality of user physiological data records to a plurality of user cohort labels, output, from the index classifier, a physiologically linked web index, receive, from the user, a search query, and generate, using the physiologically linked web index and the search query, a ranked search result.