Date

Description

Bibliography

Slides

22/01/2024

What is data mining on the Web/ Introductory lecture

Chapter 1, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Optional Reading:

• Mining the past to determine the future: problems and possibilities, D. J. Hand, International Journal of Forecasting, 25(3), 441-451, 2009.

Lecture 1

25/01/2024

Map-Reduce Framework

Chapter 2, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Optional Reading:

• Feng Li, Beng Chin Ooi, M. Tamer Özsu, and Sai Wu. 2014. Distributed data management using MapReduce. ACM Comput. Surv. 46, 3, Article 31 (January 2014), 42 pages. 
• Jeffrey Dean and Sanjay Ghemawat. (2004) MapReduce: Simplified Data Processing on Large Clusters. Proceedings of the 6th Symposium on Operating System Design and Implementation (OSDI 2004), pages 137-150.
• Sanjay Ghemawat, Howard Gobioff, and Shun-Tak Leung. (2003) The Google File System. Proceedings of the 19th ACM Symposium on Operating Systems Principles (SOSP-03), pages 29-43.
• Lin & Dyer, Chapter 2, MapReduce Basics

Lecture 2

29/01/2024

Frequent itemsets and Association rules

Chapter 6, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Optional Reading:

• Rakesh Agrawal and Ramakrishnan Srikant: Fast Algorithms for Mining Association Rules. In International Conference on Very Large Databases, VLDB 1994.

Lecture 3

01/02/2024

Frequent itemsets and Association rules

Chapter 6, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 4

05/02/2024

Finding Similar Items

Chapter 3, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 5

08/02/2024

Finding Similar Items

Chapter 3, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 6

15/02/2024

Clustering

Chapter 7, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 7

19/02/2024

Clustering

Chapter 7, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Optional Reading:

• Jain, A. K., Murty, M. N., and Flynn, P. J. 1999. Data clustering: a review. ACM Comput. Surv. 31, 3 (Sep. 1999), 264-323.

Lecture 8

22/02/2024

Recommendation Systems

Chapter 9, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Optional Reading:

• The Long Tail in Wired
• Netflix Challenge

Lecture 9

26/02/2024

Dimensionality Reduction

Chapter 9, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Optional Reading:

• For Petros Drineas’ tutorials on linear-algebra methods for data mining see here.
• Singular Value Decomposition by Yan-Bin Jia
•  M. Brand. Fast online svd revisions for lightweight recommender systems. In Proceedings of the 3rd SIAM International Conference on Data Mining, 2003.

Lecture 10

29/02/2024

Mining Data Streams

Chapter 4, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 11

4/03/2024

Mining Data Streams

Chapter 4, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 12

07/03/2024

Midterm

Chapters: 1, 2, 3, 6, 7, 9

Midterm sample

11/03/2024

Link Analysis and Web search

Chapter 5,Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Optional Reading:

• Anatomy of a large-scale hypertextual Web search engine, original paper from 1998 by Brin and Page on PageRank
• Deeper inside PageRank, Langville and Meyer, 2004
• A Survey of Eigenvector Methods for Web Information Retrieval, Langville and Meyer, 2005, SIAM Review
• Link analysis for the Web graph, chapter 21 from Introduction to Information Retrieval by Manning, Raghavan, and Schutze

Lecture 13

14/03/2024

Link Analysis and Web search

Chapter 5, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 14

21/03/2024

Advertising on the Web

Chapter 8, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 15

28/03/2024

Learning through Experimentation 

Chapter 8, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Multi-armed bandit problem (wikipedia)

A Contextual-Bandit Approach to Personalized News Article Recommendation by Li, Chu, Langford, Schapier. WWW 2010.

Lecture 16

04/04/2024

Large-Scale Machine Learning

Chapter 12, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 17

8/04/2024

Mining Social-Network Graphs

Chapter 10, Mining Massive Datasets, by Jure Leskovec, Anand Rajaraman and Jeff Ullman, Cambridge University Press, 2014

Lecture 18

11/04/2024

Data Privacy

Lecture 19

15/04/2024

Project Presentations

18/04/2024

Projects Presentations