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Probabilistic Latent Semantic Analysis / Indexing - Introduction

But I recently found this link very useful for understanding LSA principles without too much math. http://www.puffinwarellc.com/index.php/news-and-articles/articles/33-latent-semantic-analysis-tutorial.html . It creates a good foundation on which I can build on.

I'm currently looking for a similar introduction to probabilistic latent semantic analysis / indexing. Less mathematics and more examples explaining the principles underlying it. If you knew such an introduction, please let me know.

Is it possible to use a measure of similarity between sentences? Does it handle polysemy?

Is there a python implementation for the same?

Thank.

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There is a good talk by Thomas Hoffman that explains both the LSA and its relation to probabilistic latent semantic analysis (PLSA). There is math in the conversation, but it is much easier to follow than a PLSA document (or even its Wikipedia page).

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