Abstract: A system includes a computing platform having a hardware processor and a memory storing software code and a machine learning (ML) model trained to predict the next element of a sequence. The software code is executed to receive input data identifying an element of the sequence, determine, using the input data, at least one mood driver(s) of the sequence, and predict, based on input data and the mood driver(s), one or more candidate next element(s) of the sequence using the ML model. The software code further obtains expertise data relating to the sequence, evaluates the candidate next element(s), using the expertise data, the input data, and the mood driver(s), to provide aptness score(s) each corresponding to a respective one candidate next element, and determines, using the aptness score(s) and a respective probability assigned to each of the candidate next element(s) by the ML model, the next element of the sequence.