| CPC G06F 16/119 (2019.01) [G06F 3/0604 (2013.01); G06F 3/0647 (2013.01); G06F 3/067 (2013.01); G06F 16/35 (2019.01); G06F 30/27 (2020.01); G06F 16/908 (2019.01)] | 18 Claims |
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1. A machine learning-based method for migrating digital items, the method comprising:
accessing a corpus of digital items comprising a plurality of distinct digital items stored within a source data storage system, wherein accessing the corpus of digital items includes:
identifying a data handling queue at a remote data handling service; and
enqueuing a copy of each of the plurality of distinct digital items of the corpus of digital items within the data handling queue,
wherein the computing the classification inference is performed while each of the plurality of distinct digital items is enqueued within the data handling queue;
for each distinct digital item of the plurality of distinct items:
(i) computing, via one or more machine learning classification models, an classification inference;
(ii) identifying one or more automated handling tasks of a plurality of distinct handling tasks based on the classification inference;
(iii) executing the one or more automated handling tasks identified for each of the plurality of distinct items of digital item, wherein executing the one or more automated handling tasks includes:
(a) designating a storage location within a target data storage system based on the classification inference; and
(b) migrating a respective item of digital item from the source data storage system to the designated storage location within the target data storage system.
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