Abstract: At an artificial intelligence system, a baseline set of informational content elements pertaining to an item for presentation to one or more potential item consumers is identified. One or more optimization iterations are implemented. In a particular iteration, a data set comprising interaction records of a target audience with the baseline set and with one or more variants of the baseline set is collected. Using the data set as input to a machine learning model, effectiveness metrics of the different informational elements are determined. A particular content element set to be presented to an audience is identified using the effectiveness metrics.

Abstract: At a network-accessible artificial intelligence service for generating content-based recommendations based on multi-perspective learned descriptors, text sections associated with a plurality of description perspectives, including a single-character perspective and a multi-character perspective, are extracted from various text sources. Using the text sections as input, a machine learning model which includes respective portions corresponding to the different perspectives is trained to reconstruct the input using intermediary descriptors learned from the input. An indication that a second text source is recommended with respect to a first text source is generated using a set of the learned descriptors and transmitted.