Topic Modeling and Document Classification with MALLET (Digital Humanities Workshop Series: Text/Data)
Participants in this session will acquire a general understanding of topic modeling, the automated analysis technique often referred to as "text mining." Topic modeling can refer to a number of different algorithms, which are computationally intensive and mathematically complex. To facilitate a hands-on approach with a focus on process, this workshop uses the open-source MALLET toolkit as a platform for exploring topic modeling with LDA (Latent Dirichlet Allocation) and will not offer a comparison of algorithms. In addition to topic modeling, this session introduces the concepts of sequence labeling and automated document classification, both of which are also possible with MALLET.
** This workshop is offered for RCR credit as GS712.19. Participants who plan to receive RCR credit (as indicated on the registration form) will receive priority registration.
- Wednesday, March 7, 2018
- 9:00am - 11:00am
- Bostock 121 (Murthy Digital Studio)
- West Campus
- Digital Scholarship