Active Learning with Constrained Topic Model

Abstract

Latent Dirichlet Allocation (LDA) is a topic modeling tool that automatically discovers topics from a large collection of documents. It is one of the most popular text analysis tools currently in use. In practice however, the topics discovered by LDA do not always make sense to end users. In this extended abstract, we propose an active learning framework… (More)

Topics

3 Figures and Tables

Cite this paper

@inproceedings{Yang2014ActiveLW, title={Active Learning with Constrained Topic Model}, author={Yi Yang and Shimei Pan and Kunpeng Zhang}, year={2014} }