Topic Discovery — Latent Dirichlet Allocation

Topic discovery is an important research area, and one of the most important algorithms used in this field is Latent Dirichlet Allocation, which is an unsupervised learning algorithm based on statistics, and its inventor is Columbia University Professor David M Blei. In his research paper published in 2013 (click to view the paper), he gives the details of the algorithm. (He is the co-author with Andrew Ng and Michael I. Jordan) Until today, many variations of the algorithm are invented for different needs, but I mostly focused on the LDA algorithms that are capable to discover topics on short texts, such as Tweets. I will share the prominent extensions of LDA from this post.


Originally published at Emre Calisir.

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