6.864 | Fall 2005 | Graduate

Advanced Natural Language Processing

Lecture Notes

lec08.pdf

Description:

This resource discusses about Vector-based similarity measures, probabilistic similarity measures, beyond pairwise similarity, hierarchical clustering, Agglomerative clustering, clustering function, Single-Link clustering, Complete-Link clustering, K-Means algorithm, comparing clustering by set matching, distributional syntax, linear vs. hierarchical context, grammar induction, motivation, evaluation and baselines, structure search experiment, finding topology, HMM topology induction, PCFG induction, Chunk/Merge systems, and partially unsupervised learning.

Resource Type:
Lecture Notes

Course Info