MA-sLDAr: Multi-Annotator Supervised LDA for regression
MA-sLDAr is a C++ implementation of the supervised topic models with responses/target variables provided by multiple annotators with different levels of expertise, as proposed in:
- Rodrigues, F., Lourenço, M, Ribeiro, B, Pereira, F. Learning Supervised Topic Models for Classification and Regression from Crowds. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
Sample data using the MovieReviews dataset is provided here. See the readme file for a quick example on how to run MA-sLDA over this data.
Other datasets collected from Amazon Mechanical Turk are also provided below.
Please send questions and comments to rodr [at] dtu.dk