—We consider the problem of inferring and modeling topics in a sequence of documents with known publication dates. The documents at a given time are each characterized by a topic...
Iulian Pruteanu-Malinici, Lu Ren, John William Pai...
One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...
We propose a new statistical model, named Hierarchical Topic Trajectory Model (HTTM), for acquiring a dynamically changing topic model that represents the relationship between vid...
Enterprises have accumulated both structured and unstructured data steadily as computing resources improve. However, previous research on enterprise data mining often treats these ...
A semantic class is a collection of items (words or phrases) which have semantically peer or sibling relationship. This paper studies the employment of topic models to automatical...