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Temporally-ordered activity sequences are popular in many real-world domains. This paper presents an LDA-style topic model for sequences of temporal activities that captures three features of such sequences: 1) the counts of unique activities, 2) the Markov transition dependence and 3) the absolute or relative timestamp on each activity. In modeling the first two features we propose the concept of...
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