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Predictive methods for Text mining
Published on Feb 25, 20078586 Views
I will give a general overview of using prediction methods in text mining applications, including text categorization, information extraction, summarization, and question answering. I will then discus
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Chapter list
Predictive Methods for Text Mining00:05
Motivation for Text Mining01:25
Structured Data-mining03:01
Structured Data Example04:00
Unstructured Text-mining04:29
Some Problems in Predictive Text-mining06:25
The Machine Learning Approach09:21
Supervised learning10:17
Outline of the Tutorial11:20
Electronic Text12:27
An Example of XML Document13:23
Text Processing for Predictive Modeling13:52
Tokenization14:58
Issues in Tokenization16:17
Simple English Tokenization Procedure20:22
Lemmatization and Stemming22:11
Document Level Feature Representation25:46
Vector Space Document Model29:45
Removal of Stopwords38:49
Term Weighting41:29
Term Weighting in Document Retrieval45:05
Token Statistics: Zipf’s Law48:08
Summary of Document Level Feature Generation50:55
Example Feature Vector for Email Spam Detection53:09
Text Categorization55:17
Text Categorization Applications56:28
Electronic Spam Detection58:20
Taxonomy Classification01:01:10
Basic Text Categorization Framework01:02:57
Probability Calibration01:05:38
Comments on Probability Calibration01:07:18
Common Classification Methods01:09:34
Document Similarity in Vector Space Model01:09:58
Nearest Neighbor Method01:11:50
Centroid Method01:12:57
Example Feature Vector for Email Spam Detection01:16:56