| CPC G06F 16/3331 (2019.01) [G06F 16/16 (2019.01)] | 20 Claims |
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1. A method comprising:
receiving an input string comprising one or more identifiers for an operation;
searching at least one data repository for files corresponding to the one or more identifiers;
receiving one or more criteria corresponding to at least one of the one or more identifiers;
computing similarities, with one or more machine learning models, between the input string and respective ones of the files corresponding to the one or more identifiers;
ranking, with the one or more machine learning models, the files corresponding to the one or more identifiers based on the computed similarities and the one or more criteria;
grouping, with the one or more machine learning models, at least a portion of the ranked files into at least one group based on the ranking of the files using the one or more identifiers and the one or more criteria;
generating at least one division in a logical drive of the at least one data repository based on the received input string, wherein the at least one division corresponds to the at least one group and comprises at least the portion of the ranked files of the at least one group;
monitoring and determining, with the one or more machine learning models, a use of the at least one division and at least the portion of the ranked files;
predicting relevance of at least one of the at least one division and at least the portion of the ranked files to the input string based at least in part on the use, wherein the predicting is performed using another machine learning algorithm; and
inputting the predicted relevance and the input string into the one or more machine learning models to retrain the one or more machine learning models to identify and reuse files relevant to one or more additional input strings based on the use of at least one of the at least one division and at least the portion of the ranked files;
wherein the method is executed by a processing device operatively coupled to a memory.
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