Patent ID: 11967401
Assignee: KPN INNOVATIONS LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G  Y | IPC G

Claim 9:
10. A method of physiologically informed network searching, the method comprising:
receiving, at a computing device, a biological extraction from a user;
generating, by the computing device, a cohort-specific index classifier, wherein the index classifier comprises a machine-learning model trained by training data comprising a plurality of user physiological data records and a plurality of user cohort labels configured to receive biological extractions as inputs and output web search indices, the cohort-specific index classifier further comprising a classification algorithm for:
clustering a plurality of user physiological data records to a plurality of user cohort labels, wherein:
the plurality of user cohort labels is created using a feature learning algorithm configured to detect co-occurrences of sets of physiological data by:
dividing physiological data from a given user into a plurality of sub-combinations to create a plurality of physiological data sets using a cluster analysis configured to:
 generate an initial set of user cohort labels from an initial set of user physiological data of a plurality of users; and
 iteratively identify new clusters to generate new user cohort labels, wherein the physiological data is classified as a function of the generated new user cohort labels;
evaluating which physiological data sets tend to co-occur with which other physiological data sets as a function of a degree of similarity index value;

each user cohort label from the plurality of user cohort labels is correlated to the plurality of physiological data having a greatest degree of similarity to the biological extraction from the user; and

ranking the web search indices as a function of a cohort relevance heuristic;

outputting, by the computing device and from the cohort-specific index classifier, a physiologically linked web index, wherein the physiologically linked web index further comprises physiological data of past biological extractions of the user;
receiving, from the user, a search query;
determining, by the computing device, at least a hidden state as a function of the search query, wherein determining the at least a hidden state comprises:
parsing the search query into sequential tokens;
generating a hidden state model of at least a chain of tokens; and
determining the at least a hidden state as a function of the hidden state model;

generating, using the physiologically linked web index, the at least a hidden state and the search query, a ranked search result, wherein the ranking is determined by:
calculating an overall rank by aggregating a relevance rank, a keyword score, a user history rank, and an inverted index score; and
applying a weight factor to the overall rank;

receiving, from the user, the user's phenotype, wherein the user's phenotype comprises the user's behavioral history; and
removing, as a function of the user's behavioral history, specific search results from the previously generated ranked search results.