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Information Retrieval and Text Mining
Published on Feb 25, 200731136 Views
This four hour course will provide an overview of applications of machine learning and statistics to problems in information retrieval and text mining. More specifically, it will cover tasks like docu
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Chapter list
Machine Learning in Information Retrieval00:01
Motivation & Overview02:29
A Brief History of the Library 02:39
Digital Information Repositories03:23
Vannevar Bush (1945)04:23
Memex05:31
Information Retrieval06:27
Machine Learning & Information Retrieval07:40
Overview09:06
Ad Hoc Retrieval09:41
Ad Hoc Retrieval09:48
Vocabulary Mismatch Problem10:59
Search as Statistical Inference12:40
Estimation Problem15:41
Language Model Paradigm of IR16:52
Language Model Paradigm17:04
Language Model Paradigm18:48
Language Model Paradigm18:54
Unigram Model21:21
Naive Approach23:50
Laplace-Lidstone Discounting24:49
Smoothing by Interpolation26:35
Absolute Discounting28:13
Hierarchical Bayesian Estimation30:47
Hierarchical Bayesian Estimation33:14
Hierarchical Bayesian Estimation35:37
Two-Stage Smoothing37:29
Advanced Smoothing 39:40
Latent Variable Models in IR40:47
Document-Term Matrix41:04
A 100 Millionths of a Typical Document-term Matrix42:22
Matrix Decomposition43:11
Probabilistic Latent Semantic Analysis44:33