9. A computer program product stored on a non-transitory computer-readable medium that when executed by a processor, performs a method of providing a structured topic drift for a displayed set of user comments on an article, comprising: determining an ordered sequence of topical recommendations based on one or more properties of the displayed set of user comments and user characteristics using a sequential recommendation model; sampling one or more user comments for a plurality of the topical recommendations in the ordered sequence to produce a set of one or more user comments; appending, one by one, the one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments; and updating the sequential recommendation model based on a user response to the one or more user comments for each of the topical recommendations; determining a second ordered sequence of topical recommendations using the sequential recommendation model; sampling one or more user comments for a plurality of the topical recommendations in the second ordered sequence to produce a second set of one or more user comments; and appending, one by one, the second set of one or more user comments for each of the topical recommendations to bottom of the displayed set of user comments.
12. The computer program product as claimed in claim 9 , wherein updating the sequential recommendation model based on the user response comprises receiving a set of noisy observation input data, and determining, using the sequential recommendation model, a next internal state based on the noisy observation input data; and wherein the next internal state is used to determine the second ordered sequence of topical recommendations.