1. Summarization of Frequent Pattern Mining

2. What is FPM? Why being frequent is so important? Application of FPM Decision make/Business Software Debugging Bioinformatics Other data mining tasks Indexing Clustering/Classification/Association Rule

3. What have been done Frequent Itemset Mining Frequent Sequential Pattern Mining Frequent Subgraph Mining Frequent Tree Mining Mining A Single Large Graph Frequent motifs

4. FPM is a way to think B A E AB C C F B D F F D EAB A C AE D C F D A B A C E A D A B DC A AB B DD C C AB DC

5. Algorithm Foundations Apriori Property Enumeration Algorithm Level-wise search Depth-first search Data structure For Patterns For Data

6. Lattice

7. Apriori R. Agrawal and R. Srikant. Fast algorithms for mining association rules. VLDB, 487-499, 1994Fast algorithms for mining association rules

8. Resource and Tools Important FPM websites FIMI workshop website http://fimi.cs.helsinki.fi/ Mining Structure Data website http://hms.liacs.nl/graphs.html Commercial Databases Oracle, IBM DB2, SQL Server General Data Mining Information KDDNuggets (general/job/software, etc) Weka (www.cs.waikato.ac.nz/ml/weka/)

9. Why FPM does not work? Too many patterns? What can we do? Pattern Pruning Additional constraints? Pattern summarization Representative Patterns? Pattern Ranking

10. What is missing The common foundation for FPM, clustering, classification, etc… FPM formalization language/compiler/automatic discovery FPM understanding How and why they are being generated? The relationship between dataset and pattern

11. How FIM relate to the underlying structure of the dataset?