Abstract: A system and method is described for labelling data for trigger identification. The system and method comprising receiving data, transforming the data, extracting content from the data, processing data content through a classification machine learning model to receive a label, and trigger a secondary system based on the label. The system and method may further include maintaining a database of labeled data.

Abstract: A system includes a computer to implement a front-end input condensation program and a back-end machine learning program. Steps of the front-end program include receive input data and time data indicative of previous events associated with users; determine interface channels associated with modes of interface with the users and/or previous event characteristics; associate previous event data with time windows; generate user window values for the combinations of users and time windows indicating the interface channels and previous event characteristics of data within the respective time windows; and form condensed input data without raw input data having a low association with respect to preceding the subsequent event. Steps of the back-end program include receive the condensed input data and use the condensed data to generate an inference related to the subsequent event such that a time required by the machine learning algorithm to generate the inference is reduced.

Abstract: A system for reducing input data size for use in an artificial intelligence (AI) engine for predicting a subsequent event. The system includes a computer configured to implement instructions to receive input data and time data indicative of previous events associated with users. The instructions configure the system to determine interface channels associated with modes of interface with the users, previous event characteristics, or both. The system implements instructions associating previous event data with time windows. The instructions configure the system to generate user window values for the combinations of users and time windows. The user window values indicate the interface channels and previous event characteristics of data within the respective time windows. Implementing the instructions configures the system to form a first portion of the raw input data having an association value below a threshold with respect to preceding the subsequent event and generate condensed input data.

Abstract: A system for reducing the time to train a machine learning program for predicting a subsequent event. The system includes a computer configured to implement instructions to receive training data and time data indicative of training events associated with users. The instructions configure the system to determine interface channels associated with modes of interface with the users, training event characteristics, or both. The system implements instructions associating training event data with time windows. The instructions configure the system to generate user window values for the combinations of users and time windows. The user window values indicate the interface channels and training event characteristics of data within the respective time windows. Implementing the instructions configures the system to form a first portion of the raw input data having an association value below a threshold with respect to preceding the subsequent event and generate condensed training data.

Abstract: A system and method is described for labelling data for trigger identification. The system and method comprising receiving data, transforming the data, extracting content from the data, processing data content through a classification machine learning model to receive a label, and trigger a secondary system based on the label. The system and method may further include maintaining a database of labeled data.

Abstract: A system and method is described for training a machine learning model to label data for trigger identification. The system and method comprising receiving data from a database, extracting content from the data, transforming the data, clustering the data, labeling the data, creating a training dataset and a test data set, and training a classification machine learning model to label data accordingly to identify a trigger.

Abstract: A system for employing artificial intelligence to initiate a concurrent reaction according to predicted behavior is disclosed. The system includes at least one processor, a communication interface communicatively coupled to the at least one processor, and a memory device storing executable code that, when executed, causes the at least one processor to receive labeled interaction data for a group of users, receive user information for the group of users, correlate the labeled interaction data with the user information, apply a first algorithm to the correlated data to segment the users, based on the user’s segment apply a second algorithm to make a prediction about the user’s future behavior, and based on the predicted behavior trigger a concurrent communication to the user. Additionally, the system may update a user dashboard.

Abstract: A method for continuously forming wide, thin chewing gum slabs suitable for forming sheets and bands ready for packaging in an automatic wrapping machine is disclosed. The method involves compounding a chewing gum paste; extruding the formed gum paste as a wide thin slab through a die mounted on the discharge end of the extruder; cooling the extruded gum paste slab; and passing the gum paste slab through no more than two sets of calender rolls.

Abstract: An extrusion nozzle arrangement for the production of a product such as a comestible, including a multiple nozzle arrangement through which there can be fabricated a multi-layered slab of a meat analogue product. A bacon-like appearance is achieved in that each extrusion nozzle includes a narrow, elongate bottom outlet orifice arranged to extend transversely above a continually moving horizontal conveyor belt. An insert strip is arranged within the nozzle above the orifice and coextensive with the length thereof, which includes projections extending across the path of flow of the solution extruded through the orifice, with such projections being positioned in a predetermined manner along the insert strip as to cause either restrictions or directional changes in the flow of the solution egressing from the nozzle orifice.

Abstract: The selectivity of an adsorbent for the preferentially adsorbed component of a multi-component solution is improved by means of a countercurrent adsorption process coupled with a reflux operation wherein the loaded adsorption medium which is taken off stream as spent adsorbent is processed to concentrate the preferentially adsorbed component therein.