Abstract: Systems and methods for parsing a message in a conversation series is provided. This involves receiving a message, isolating the current exchange, dividing it up into sentences, and detecting the language being used. The message sentences are normalized, and any ‘speech acts’ are identified. Likewise, any ‘critical intents’ are identified. If there is no critical intent, the classification text is provided to sets of models for parallel prediction of the intent(s) of the message. Models are queried for based upon series of the conversation, the industry involved, the client the model is for, the message campaign, and any speech acts present. Mapping rules and/or prediction machine learning models are used to convert the intents into meanings, which are filtered. It is also possible to apply a decision engine policy for the determination of the meaning. This is followed by entity extraction and response generation by mapping meanings to actions.

Abstract: A modified shoelace comprising a first fastener and a second fastener; wherein the shoelace has an active area disposed on the shoelace between an uppermost first eyelet and an uppermost second eyelet when the shoelace is in a laced configuration, wherein the first fastener is secured to the shoelace outside the active area; wherein the second fastener is secured to the shoelace a loop distance from the first fastener and distal from the active area.