Topics over time: a non-Markov continuous-time model of topical trends


This paper presents an LDA-style topic model that captures not only the low-dimensional structure of data, but also how the structure changes over time. Unlike other recent work that relies on Markov assumptions or discretization of time, here each topic is associated with a continuous distribution over timestamps, and for each generated document, the… (More)
DOI: 10.1145/1150402.1150450


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