Abstract: A method and system for generating clusters for feedback data may include receiving a request for clustering feedback data, the request including one or more parameters relating to the feedback data, retrieving a plurality of vectorized feedbacks stored in a key value format, the key value format including a feedback identifier used as a key for each of the plurality of vectorized feedbacks, creating a plurality of feedback clusters based on the one or more parameters and the retrieved plurality of vectorized feedbacks, the plurality of feedback clusters categorizing at least some of the feedback data into the plurality of feedback clusters, and transmitting data relating to the plurality of feedback clusters for display on a user interface screen.

Abstract: A system and method for creating a machine learning (ML) classifier for a database uses a weakly-supervised training data set created automatically from database items on the basis of a human-created keyword set. The automatically created training data set is used to construct one or more deep learning classifier checkpoints, which can then be compared with one another and with a classifier based on the original keyword set in order to select a classifier for use by other users viewing the database.

Abstract: A system and method for creating a machine learning (ML) classifier for a database uses a weakly-supervised training data set created automatically from database items on the basis of a human-created keyword set. The automatically created training data set is used to construct one or more deep learning classifier checkpoints, which can then be compared with one another and with a classifier based on the original keyword set in order to select a classifier for use by other users viewing the database.