Interactive Topic Modeling – ITMS

Topic modeling refers to an algorithm that explains “an observed corpus with a small set of distributions over terms” and “models for uncovering underlying semantic structure of a document collection”  (Blei et al. 2003, Blei et al. 2009, Blei 2012). Several algorithms have been put forth to build a probabilistic topic model, e.g  mixture-of-unigram (Nigam et al. 2000), Latent Semantic Indexing (Deerwester et al. 1990; Hofmann 1999) and Latent Dirichlet Allocation LDA (Blei et al. 2003). For more information, see Matthew Jockers and David Blei.

Interactive Text Mining Suite applies various LDA algorithms (topicmodels, lda and stm R packages). In addition, it allows users interactively choose number of topics, iterations and select the best models.

Screen shot 2016-03-18 at 1.46.42 PMScreen shot 2016-03-18 at 1.48.48 PM

We  welcome suggestions and feedback.

Advertisements

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s