CPC G06F 16/285 (2019.01) [G06F 9/546 (2013.01); G06N 20/00 (2019.01)] | 18 Claims |
1. A computer-implemented method for clustering incoming messages, comprising:
receiving, by a machine learning (ML) engine, an incoming message from an application programming interface (API) server;
scanning, by the ML engine, a plurality of clusters for one or more messages having similar attributes or features to that of the incoming message;
identifying, by a clustering engine, a cluster from the plurality of clusters, wherein the identified cluster comprises the one or more messages similar to that of the incoming message;
receiving, by the clustering engine, positive or negative feedback from an agent;
depending on the feedback, marking, by the clustering agent, the incoming message as being mapped, or determining if the cluster being predicted has been predicted a predetermined number of times prior to receiving the negative feedback; and
creating, by the clustering engine, a new cluster and assigning the incoming message to the new cluster when the cluster is predicted for the predetermined number of times.
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