Review on MALLET by Donald Vargas

The support team was great! They were always willing an eager help us with any questions that we had regarding Mallet's implementation of Latent Dirichlt Model Analysis (LDA). I have no issues at all using mallett or anything else from them in our organization so far as software products go but if you are looking into purchasing this product look elsewhere because they do not offer their own training program - which can be quite costly when compared against similar programs like LIWC etc.- It could take some time getting used too since there isn't much documentation out here yet. We use latent dirchlick model analysis tool within mallette specifically through its API called java api client 1.0 to analyze content across multiple data sets such has Twitter feeds/tweets to understand sentiment towards different topics within tweets over several years period during specific events e.g. elections vs hurricane relief efforts & more importantly how those changes evolved overtime versus comparing one event year wise vs two distinct election cycles. It's easy to use, easy to install, and very flexible, so you can customize your own training data or even train yourself by feeding in examples of your own sentences. I have trained an NLU model with Mallet to understand user intent from chatbot conversations, but haven't used it much since then. This feature has been useful when I needed to look up a word's meaning quickly.