1. A method for training a topic model, comprising: for respective documents within a document corpus: receiving a document representation of a document and features of the document, the document representation comprising a frequency of word occurrences within the document; processing the document representation and the features using a topic model, the processing comprising: specifying feature/topic parameters for respective features of the document, a feature/topic parameter specifying a distribution of probabilities of a feature being indicative of one or more topics, the feature/topic parameter based upon a first uncertainty measure; and specifying document/word/topic parameters for respective words within the document, a document/word/topic parameter specifying a distribution of probabilities of a word being indicative of one or more topics, the document/word/topic parameter based upon a second uncertainty measure; and training the topic model based upon the specified feature/topic parameters and the specified document/word/topic parameters.