Modeling discrete dynamic topics
Seyed Ali Bahrainian, Ida Mele, Fábio Crestani · 2017
Topic modeling is an important area which aims at indexing and exploring massive data streams. In this paper we introduce a discrete Dynamic Topic Modeling (dDTM) algorithm, which is able to model a dynamic topic that is not necessarily present over all time slices in a stream of documents. Our proposed model has applications in modeling dynamic topics of rapidly changing and less structured data, such as online microblogs and news streams.