| CPC G06F 16/122 (2019.01) [G06F 16/18 (2019.01)] | 19 Claims |
|
1. A method implemented by one or more processors, the method comprising:
receiving information identifying a document and a set of folders;
for each folder in the set of folders, using a trained model to predict a similarity measure between the folder and the document, wherein using the trained model to predict the similarity measure for each folder comprises:
processing, using the trained model, one or more folder features of the folder along with one or more document features of the document; and
generating the similarity measure for the folder based on the processing;
for each folder in the set of folders, determining a score for the folder based on the predicted similarity measure for the folder and a folder weight, wherein the folder weight is based on a frequency of access for the folder or a number of files in the folder;
selecting a candidate folder from the set of folders using the scores of the folders within the set of folders;
providing, on a user interface, a selectable option to associate the document with the candidate folder;
receiving an indication of acceptance of the selectable option to associate the document with the candidate folder; and
in response to (i) providing the selectable option to associate the document with the candidate folder and (ii) receiving the indication of acceptance of the selectable option to associate the document with the candidate folder, labeling the document with a training label based on the indication of acceptance of the selectable option to associate the document with the candidate folder, and using the document labeled with the training label to further train the trained model.
|