Lecture Notes



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.

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