Resources

Conference calls & deadlines

WikiCFP data mining KDnuggets

Reading material

Data Mining

• "Introduction to Data Mining", Pang-Ning Tan, Michael Steinbach, Vipin Kumar, 2005.
• "Data Mining: Concepts and Techniques, 3rd ed.", Jiawei Han, Micheline Kamber and Jian Pei, 2012.
• "Data Mining and Analysis" (available online), Mohammed Zaki, Wagner Meira, Cambridge University Press, 2014.

Frequent Itemsets Mining

• "Algorithms for association rule mining - a general survey and comparison", Hipp et al., SIGKDD Exploration Newsletter, 2000.
• "Frequent Pattern Mining: Current Status and Future Directions", Han et al., DMKD, 2007.
• "FIM Repository" for datasets and algorithm implementations.

Clustering

• "Data Clustering: A Review", Jain et al., ACM Computing Surveys, 1999.

Classification

• "Classification: Basic Concepts, Decision Trees, and Model Evaluation", Chapter 4 from the Introduction to Data Mining book by P.-N. Tan, M. Steinbach, V. Kumar.
• "Classification and Regression: Money *Can* Grow on Trees", Gehrke et al., KDD tutorial, 1999.
• "Advances in Decision Tree Construction", Gehrke and Loh, KDD tutorial, 2001.

Datasets

• UCI Machine Learning Repository
• UCI KDD Archive
• Datasets in .arff format (for WEKA, MOA)
• FIM Repository for frequent itemsets mining datasets.

Tools

• WEKA: DM software for clustering, classification, frequent itemsets minining (in Java).
• MOA: An extension of WEKA for streams. Support for clustering, classification (in Java).
• ELKI: DeveLoping KDD-Applications Supported by Index-Structures (in Java).

Misc

• ACM Special Interest group in Data Mining
• Women in Machine Learning
• Video lectures net
• WORDLE: Beautiful word clouds generator.