Text Mining / Web Mining

10/11/99


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Table of Contents

Text Mining / Web Mining

Text Mining as a Data Mining Task

Applications

KDD Process

Data Preparation

Feature Selection

Missing Data

Why Text is Rich to Mine

Why Text is Tough to Mine

Classify documents

Discovering Trends in Text

Hierarchy of Phrases

Grow Sequences

Shape Matching

Data Mining to Create Taxonomy

TAPER

Querying

Improved query environment

Document signature

TAPER Algorithm

Feature Selection

Number of Features

Hierarchical Classification

Hierarchical Classification

Results

Results - Confusion Matrices

Results of Hierarchical Classification

Organization of Web Pages Using WordNet and Self-Organizing Maps

Test Pages

Overall Process

WordNet

Creating Feature Vectors

Self-Organizing Map

Maps

Sammon Map

Results

In the Spotlight

In the Spotlight

WWW Data Mining

Challenges to Web Mining

Web Mining: Much Can Be Done!

Web Log Mining

A Multiple Layered Meta-Web Architecture

Future

Author: Diane J. Cook