UTCS Artificial Intelligence
HFM: Hierarchical Features Maps
Active from 1989 - 1994
If the data is strongly hierarchical, visualizing it on a flat SOM may make the hierarchy hard to see. With HFM, a hierarchy of maps is self-organized, with the high-level categories separated on top, and gradually more fine distinctions in the bottom. For example script-based story data can be visualized this way, and it forms a good foundation for episodic memory organization in story processing (see the NLP page).
risto [at] cs utexas edu
Unsupervised Learning, Clustering, and Self-Organization