COMP5331 Advanced Topics Prepared by Raymond Wong

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COMP5331 Advanced Topics Prepared by Raymond Wong Presented by Raymond Wong raywong@cse COMP5331

Topics in Project Presentation Topics in Lectures Fundamental topics in data mining Topics in Project Presentation Advanced topics in data mining But, they need “concepts” from fundamental topics COMP5331

Advice for Project Presentation It is not compulsory to attend It is good to attend to broaden your horizon COMP5331

Topics Association/Frequent Itemset Clustering How to represent frequent itemsets? (e.g., maximal frequent itemsets and regular itemsets) Clustering How to perform subspace clustering? (e.g., how to find some interesting subspaces) COMP5331

Topics Classification Data Warehouse How to train a “group” of classifiers (or ensemble)? (e.g., multi-task learning) Data Warehouse How to create the data warehouse over different types of data (e.g., graph data)? COMP5331

Topics Data Streams Web DB How to perform new data mining tasks over data streams? Web DB A hot topic (e.g., name ambiguation) COMP5331

Topics Decision-Making Pattern-based mining (e.g., skyline and periodic patterns) COMP5331

Other Hot Topics Social Network Privacy Issues How people are connected (e.g., facebook)? Privacy Issues How to protect privacy for data mining? COMP5331

Other Hot Topics Graph Data Deep Learning How to analyze the graph data in a meaning way? Deep Learning How to use deep learning in different applications? COMP5331

Final Issues 3 Assignments 1 Project Enough? Difficult? With a lot of in-class exercises. 1 Project Difficult? Depends on you! COMP5331

Final Issues In-class Participation Enough? Please continue! COMP5331

One final issue Work hard for your exam and your project!  COMP5331