11 -Introduction to Topic Modeling

To determine the similarity of words based on the documents they cooccur in and the similarity of documents based on the words they contain.

It helps in obtaining the best (least-squares) approximation by truncating the matrix to topics.

By approximating it using Monte-Carlo sampling if only a certain number of components are needed.

<p>Every document and every word is considered as a mixture of topics.</p> Signup and view all the answers

<p>For every document: a topic distribution, and for every word: a word distribution for every topic.</p> Signup and view all the answers

<p>No, SVD does not yield probabilities directly, but the factors obtained can contain negative values.</p> Signup and view all the answers

<p>Find the latent structure that resembles topics and best summarizes the collection.</p> Signup and view all the answers

<p>It helps address challenges like synonymy and polysemy in information retrieval.</p> Signup and view all the answers

<p>In clustering, the emphasis is on data points/documents, while in topic modeling, the emphasis is on the topics/clusters themselves.</p> Signup and view all the answers

<p>Exact search will not find synonyms and will include polynyms and homonyms.</p> Signup and view all the answers

<p>Factors provide a lower-dimensional representation of the document.</p> Signup and view all the answers