Sentiment-based recommendations as a function of grounding factors associated with a user

A system, comprising:

• a general purpose computing device;
• and
• a computer program executable by the computing device, wherein the computing device is directed by the computer program to:
• receive a machine-learned facet model trained on a plurality of examples of training data;
• the plurality of examples of training data comprising a plurality of automatically clustered and labeled instances of sentiment vocabulary extracted from sentiment bearing content;
• apply the machine-learned facet model to sentiment-bearing content to identify and label facets for each conversational topic associated with those facets, and to identify corresponding sentiments;
• generate a plurality of sentiment-based recommendations about one or more of the identified facets that have a consensus;
• and
• generate multiple sentiment-based recommendations that are consistent with the identified corresponding sentiments and that are further consistent with one or more grounding factors associated with a user;
• and
• present one or more of the sentiment-based recommendations to the used.

A portable computing device comprising:

• a memory configured to store a computer program;
• and
• a processing unit configured to execute the computer program, thereby causing the computing device to:
• receive a machine-learned facet model automatically generated by applying one or more automated machine-learning processes to a plurality of examples of training data comprising a plurality of automatically clustered and labeled instances of sentiment vocabulary extracted from sentiment bearing content;
• apply the machine-learned facet model to identify conversational topics and facets associated with one or more segments of a plurality of samples of sentiment-bearing content;
• determine a consensus for one or more identified facets, the consensus for each facet being based on two or more samples of the sentiment-bearing content;
• generate a plurality of recommendations about one or more of the identified facets, each of the recommendations being consistent with the corresponding consensus and further being consistent with one or more grounding factors associated with a user;
• identify one or more of the recommendations that are relevant to a user;
• and
• present one or more of the relevant recommendations to the user in the form of a conversational utterance provided via a combined audio and video display of a digital avatar.