Patent ID: 11915113
Assignee: VERINT AMERICAS INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. A system for scaling active learning across a distributed active learning system, the system comprising:
a memory comprising executable instructions;
a plurality of distributed processing devices; and
a first processor configured to execute the executable instructions and cause the system to:
select a distributed query strategy for application to a pool of unlabeled data and partitioning the pool into a predetermined number of subsets of unlabeled training data;
allocate each of the predetermined subsets to a respective one of the plurality of distributed processing devices;
apply the distributed query strategy, wherein the selected distributed query strategy comprises a predetermined number of tasks, wherein the predetermined number of tasks equals the predetermined number of subsets, and wherein the query strategy is adapted to work in parallel across the plurality of distributed processing devices; and
receive from each of the plurality of distributed processing devices a predetermined number (n) of resulting unlabeled samples after the selected query strategy is performed by the plurality of distributing processing devices, wherein confidence in the resulting unlabeled samples, determined by a machine learned model, is lowest;
provide the resulting unlabeled samples for labeling to generate labeled selected samples;
receive the labeled selected samples, and
retrain the machine learned model using the labeled selected samples.