Explainers

These guides provide detailed walkthroughs of key text analysis concepts and techniques used in this course.

Available Guides

1. Text Analysis Basics

Introduction to fundamental concepts in computational text analysis, including preprocessing, tokenization, and the bag-of-words model.

2. Clustering

Overview of clustering methods for grouping similar documents, including hierarchical clustering and k-means.

3. Clustering Expanded

Deeper exploration of clustering techniques, interpretation strategies, and practical considerations.

4. Topic Modeling

Guide to topic modeling with Latent Dirichlet Allocation (LDA), including how to interpret and evaluate topic models.

These explainers supplement the class presentations and Orange Data Mining tutorials.