A study on dual topic models and bayesian topic model inference - Rugeles, Daniel (Nanyang Technological University, 2020)
Topic models have been shown to be a powerful tool for organizing large collections of unstructured data, including text, images and location data. The essence of the topic model is to discover hidden clusters that summarize the relationship between two discrete random variables, such as documents and words in text data, or users and places in location data. In the former case, a topic typically refers to a cluster of semantically related words and the documents are described using the extracted topics.