Project details for Multi Annotator Supervised LDA for regression

Logo Multi Annotator Supervised LDA for regression 1.0

by fmpr - January 16, 2017, 18:10:19 CET [ Project Homepage BibTeX BibTeX for corresponding Paper Download ]

view (1 today), download ( 0 today ), 0 subscriptions

Description:

MA-sLDAr is a C++ implementation of the supervised topic models with response 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 multiple-annotator data using the MovieReviews dataset and more datasets are available here: http://www.fprodrigues.com/software/

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download
Corresponding Paper BibTeX Entry: Download
Supported Operating Systems: Linux, Mac
Data Formats: Various
Tags: Topic Modeling, Supervised Learning, Crowdsourcing
Archive: download here

Other available revisons

Version Changelog Date
1.0

Initial Announcement on mloss.org.

January 16, 2017, 18:10:19
v1.0

Initial Announcement on mloss.org.

January 16, 2017, 18:07:16

Comments

No one has posted any comments yet. Perhaps you'd like to be the first?

Leave a comment

You must be logged in to post comments.