Learning a Concept Hierarchy from Multi-labeled Documents
Viet-An Nguyen, Jordan L. Ying, Philip Resnik, Jonathan Chang
–Neural Information Processing Systems
While topic models can discover patterns of word usage in large corpora, it is difficult to meld this unsupervised structure with noisy, human-provided labels, especially when the label space is large.
Neural Information Processing Systems
Feb-9-2025, 04:41:54 GMT
- Country:
- Africa > Middle East
- Egypt (0.04)
- Libya > Benghazi District
- Benghazi (0.04)
- Tunisia (0.04)
- Asia
- Afghanistan (0.04)
- China > Tibet Autonomous Region (0.04)
- Middle East
- North Korea (0.14)
- Pakistan (0.04)
- Taiwan (0.04)
- Vietnam (0.04)
- Europe
- Albania (0.04)
- North Macedonia (0.04)
- United Kingdom > England
- Cambridgeshire > Cambridge (0.04)
- North America
- Central America (0.04)
- Cuba > Guantánamo Province
- Guantánamo (0.04)
- Haiti (0.04)
- United States
- California > San Mateo County
- Menlo Park (0.04)
- Colorado > Boulder County
- Boulder (0.14)
- Maryland > Prince George's County
- College Park (0.14)
- California > San Mateo County
- South America (0.04)
- Africa > Middle East
- Industry:
- Government
- Law (0.94)
- Law Enforcement & Public Safety (0.68)
- Technology: