Abstract: The systems and methods provide an action recognition and analytics tool for use in manufacturing, health care services, shipping, retailing and other similar contexts. Machine learning action recognition can be utilized to determine cycles, processes, actions, sequences, objects and or the like in one or more senor streams. The sensor streams can include, but are not limited to, one or more video sensor frames, thermal sensor frames, infrared sensor frames, and or three-dimensional depth frames. The analytics tool can provide for contextual training using the one or more sensor streams and machine learning based action recognition.

Abstract: Example processes for determining a match type include: receiving a query token from a content provider; consulting a database stored in memory to determine past performance of the query token for associated content, where the past performance includes performance information indicating how well the query token performed for different match types, where a match type indicates a way that components of the query token match components of another query token in order to achieve a token match; determining, based on the performance information, differences in performance between ones of the different match types; comparing the differences in performance to a threshold; and selecting a match type for the query token based on the comparing.