Topic Modeling of Online Accommodation Reviews via Latent Dirichlet Allocation

Automatic keyword extraction using Latent Dirichlet Allocation topic modeling: Similarity with golden standard and users' evaluation

Purpose: This study investigates the automatic keyword extraction from the table of contents of Persian e-books in the field of science using LDA topic modeling, evaluating their similarity with golden standard, and users' viewpoints of the model keywords. Methodology: This is a mixed text-mining research in which LDA topic modeling is used to extract keywords from the table of contents of sci...

Topic Models - Latent Dirichlet Allocation

Scalable Dynamic Topic Modeling with Clustered Latent Dirichlet Allocation (CLDA)

Topic modeling is an increasingly important component of Big Data analytics, enabling the sense-making of highly dynamic and diverse streams of text data. Traditional methods such as Dynamic Topic Modeling (DTM), while mathematically elegant, do not lend themselves well to direct parallelization because of dependencies from one time step to another. Data decomposition approaches that partition ...

Latent Dirichlet Allocation For Text And Image Topic Modeling

Latent Dirichlet allocation (LDA) is a popular unsupervised technique for topic modeling. It learns a generative model which can discover latent topics given a collection of training documents. In the unsupervised learning framework, where the class label is unavailable, it is less intuitive to evaluate the goodness-of-fit and degree of overfitting of learned model. We discuss two measurements ...

Assignment 2: Twitter Topic Modeling with Latent Dirichlet Allocation Background

In this assignment we are going to implement a parallel MapReduce version of a popular topic modeling algorithm called Latent Dirchlet Allocation (LDA). Because it allows for exploring vast document collection, we are going to use this algorithm to see if we can automatically identify topics from a series of Tweets. For the purpose of this assignment, we are going to treat every tweet as a docu...