This paper presents a user recommendation system that recommends to a user new friends having similar interests. We automatically discover users’ interests using Latent Dirichle...
Users of topic modeling methods often have knowledge about the composition of words that should have high or low probability in various topics. We incorporate such domain knowledg...
The article contributes a derivation of variational Bayes for a large class of topic models by generalising from the well-known model of latent Dirichcation. For an abstraction of ...
Document collections evolve over time, new topics emerge and old ones decline. At the same time, the terminology evolves as well. Much literature is devoted to topic evolution in ...
Low-dimensional topic models have been proven very useful for modeling a large corpus of documents that share a relatively small number of topics. Dimensionality reduction tools s...