Abstract: Systems and methods are disclosed for analyzing a customer review of a product includes extracting product categories and predicates from the customer review; extracting product features from the customer review; extracting an activity with the product features from the customer review; performing sentiment analysis using a learning machine on the customer review; determining a life scene from the customer review; and analyzing a customer opinion from the customer review.

Abstract: A system and method to receive user input from a human user in a communication session between the human user and a first machine; autonomously determine a sentiment metric of the user input from the human user based on one or more sentiment criteria, wherein the sentiment metric represents an attitude of the human user; autonomously determine a quality metric associated with the communication session; autonomously rank the communication session between human user and first machine based on one or more of the sentiment metric and the quality metric; and determine based on the ranking, to recommend human agent intervention in the communication session between the human user and the first machine.