Human-Centric Topic Modeling with Goal-Prompted Contrastive Learning and Optimal Transport

1. 1Define a human-provided goal for topic modeling
2. 2Implement goal-prompted contrastive learning to integrate the goal into the topic modeling process
3. 3Apply optimal transport to ensure diverse and interpretable topics
4. 4Evaluate the resulting topics using metrics such as coherence and diversity
5. 5Refine the topic model by adjusting the goal and optimal transport parameters

Data scientists and NLP engineers can benefit from this approach to improve topic modeling in their applications, especially when working with users who have specific goals in mind

💡 Integrating human-provided goals into topic modeling can produce more interpretable and diverse topics

📊 Improve topic modeling with human-centric approach using goal-prompted contrastive learning and optimal transport! #NLP #TopicModeling