Probabilistic Latent Semantic Analysis (PLSA)

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PLSA is a probabilistic generative model used for topic modeling in text data. It is an extension of Latent Semantic Analysis that introduces a probabilistic framework to the topic modeling problem. How PLSA Works: In PLSA, it is assumed that documents are generated through a probabilistic process. Specifically, it assumes that there are latent topics, and each document is a mixture of these topics. Each word in a document is generated from one of these topics with a certain probability. Applications: PLSA is mainly used for discovering topics in large document collections. By analyzing the word-topic and topic-document distributions learned by PLSA, you can identify the prevalent themes or topics within the corpus.