3. The method as claimed in claim 1 , wherein determining the ordered sequence of topical recommendations further comprises determining one or more features associated with the structured topic drift using a prediction function in the sequential recommendation model; determining, using the sequential recommendation model, an initial internal state based on the one or more features, wherein the initial internal state is related to the user characteristics and is used to determine the ordered sequence of topical recommendations.
3. The method as claimed in claim 1 , wherein determining the ordered sequence of topical recommendations further comprises determining one or more features associated with the structured topic drift using a prediction function in the sequential recommendation model; determining, using the sequential recommendation model, an initial internal state based on the one or more features, wherein the initial internal state is related to the user characteristics and is used to determine the ordered sequence of topical recommendations. 5. The method as claimed in claim 3 , wherein the features associated with the structured topic drift comprise at least one of an effortless topic transition, a relevance to the displayed set of user comments to the user preferences, and a current determination of the structured topic drift.