Patent ID: 11886523
Assignee: DELL PRODUCTS L.P.
Field: Computer technology (Electrical engineering)
Classification: CPC G  H | IPC G

Claim 16:
17. A method for using a trained machine learning (ML) algorithm that has been trained to identify correlations between a new search session and previously learned search sessions in order to provide refined search results for the new search session, where the refined search results are designed in an attempt to reduce a number of webpage navigations that will potentially be performed during the new search session and where the refined search results are generated based on webpage navigations that were tracked as parts of the previously learned search sessions, said method comprising:
detecting a search starting event for the new search session, wherein the search starting event is identified (i) based on a detection of one or more search terms being entered in a browser to facilitate execution of an initial search or (ii) based on the execution of the initial search;
causing the trained ML algorithm to attempt to identify correlations, wherein the correlations include correlations between (i) the one or more search terms and (ii) one or more previous navigations between various webpages, where the one or more previous navigations were tracked as parts of the previously learned search sessions, and wherein the correlations include correlations between characteristics of a user who is conducting the new search session and characteristics of users who conducted the previously learned search sessions;
generating a set of search results based on the one or more search terms and further based on a set of correlations identified by the trained ML algorithm; and
based on new data collected during the new search session, causing the ML algorithm to further generate search results that are generated based on one or more new correlations that are identified by the trained ML algorithm.