Tentative Schedule

EE 380L – A Practicum in Data Mining

CS 395T /CAM 395T – Large-Scale Data Mining

 

1/17                   Introduction

 

1/22 – 1/31        Hyperlinks on the web

• Hubs & Authorities

• Linear Algebra Refresher

• Google’s PageRank Algorithm

• Web Structure (Bowtie)

2/5                   Student Paper Presentations

 

2/7 – 2/21         Information Retrieval I

• Overview

• Representations

• Querying

• Clustering

• EM

2/26                 Student Paper Presentations

 

2/28 – 3/19       Information Retrieval II

• Graph Partitioning

• Classification

---

3/21                 Clustering

3/26                 Classification (Naive Bayes, Fisher's LDA, Neural Network Classifiers)

3/28                 Student paper presentations

4/2                   Clickstream Analysis (Goals, Pre-processing, Cowpath Analysis)

4/4                   No Lecture

4/9                   Exam

4/11                 Clickstream Analysis and Personalization

4/16                 SVM (by Arindam) followed by 1 or 2 student presentations

4/18                 Student paper presentations

4/23                 Personalization ( Recommender Systems, System Issues, Personal Agents,
                        Multi-method Personalization)

4/25 - 5/2         Misc. (project presentations, etc.)