Abstract: Methods and apparatuses are described for predicting compliance of text documents with a ruleset using self-supervised machine learning. A server executes an NLP teacher model on first unlabeled sentences to generate a first compliance pseudo-label for each first unlabeled sentence. The server trains an NLP student model using the first unlabeled sentences and first compliance pseudo-labels, including injecting input noise by aggregating each unlabeled sentence with one or more sentences adjacent to each unlabeled sentence into a sentence block and providing the aggregated sentence blocks as input to train the NLP student model. The server executes the trained NLP student model, using second unlabeled sentences, to generate a second compliance pseudo-label for each second unlabeled sentence. The server determines compliance of the second sentences with one or more rulesets using the second compliance pseudo-labels.

Abstract: The technology described herein provides a point of decision display system and method that delivers an interactive advertisement to a consumer when the consumer is in the process of making a decision. The system includes: a display system controller, a video display device to display an interactive advertisement to a consumer when the consumer is in a process of making a decision, an audio output device to provide audio for the interactive advertisement to the consumer, a sensor processing unit to trigger the display system controller to display the interactive advertisement to the consumer, a presence sensor to sense the consumer in the process of making the decision, and a content delivery server to provide content through the display system controller and video display device to the consumer.