Title:  Frequent Pattern Mining for Association Rule Generation

Speaker: Dr. Ghada Badr

Abstract:

Frequent patterns are patterns (such as itemsets, subsequences, or substructures) that appear in a data set frequently. For example, a set of items, such as milk and bread, that appear frequently together in a transaction data set is a frequent itemset. A subsequence, such as buying first a PC, then a digital camera, and then a memory card, if it occurs frequently in a shopping history database, is a (frequent) sequential pattern. A substructure can refer to different structural forms, such as subgraphs, subtrees, or sublattices, which may be combined with itemsets or subsequences. If a substructure occurs frequently, it is called a (frequent) structured pattern. Finding such frequent patterns plays an essential role in mining associations, correlations, and many other interesting relationships among data. Moreover, it helps in data classification, clustering, and other data mining tasks as well. Thus, frequent pattern mining has become an important data mining task and a focused theme in data mining research.
In this talk, I will introduce the concepts of frequent patterns, associations, and correlations, and study how they can be mined efficiently. The topic of frequent pattern mining is indeed rich.  If time permits, we can delve into the following questions: How can we find frequent itemsets from large amounts of data, where the data are either transactional or relational? How can we mine association rules? Which association rules are the most interesting?  How can we take advantage of user preferences or constraints to speed up the mining process?

Speaker's Bio: Dr Ghada Badr completed her Ph.D. in 2006 in Computer Science at Carleton University, School of Computer Science, Ottawa, Canada, in Information retrieval and Syntactic Pattern Recognition. She finished her degree with high honor and was the winner of the university Senate Medal for outstanding research achievements. Her Ph.D. Thesis included a lot of applications in Bioinformatics for searching and storing DNA sequences. In 2006- 2007, she worked as a research associative at the National Research Council (NRC) of Canada for the language technology group in Gatineau, Canada, in the field of Machine Translation. There, she was able to apply a lot of the techniques that she developed during her Ph.D. In 2007, she won the prestigious NSREC Postdoctoral Fellowship in Canada. In 2007-2011, she worked as a Postdoctoral fellow at the University of Ottawa, Ottawa, Canada, where she conducted her research in the field of Bio-informatics and more specifically in Genome Rearrangement projects. Concurrently, she worked in another research project, where it involves processing of interacting RNAs. The project should result in a tool for muti-pattern processing in multi-sequences, which should have great benefits for computer scientists and biologists working in the field. Every single work was highly recognized and published in high rank journals and conferences such as ACM, IEEE, the Computer Journal, the PAA journal, and BMC Algorithms for Molecular Biology. Writing and documenting research achievements need a lot of experience and skills. She acquired these skills by being totally involved in writing my grant applications, patent application, posters, presentations, and all her paper publications. Her paper, published in the Computer Journal, was the winner of the Wilkes paper award in 2006 and was cited as the Most Meritorious.

At KSU, she was able to establish the Bioinformatics Research group (BioInG), where she is the coordinator for the group since Fall 2012. Through the group she was able to attract a lot of researchers from different departments and to develop a lot of activities and workshops. Please refer to the group website (http://bioinformaticksurg.blogspot.com) for more information. She is also the Head of the CCIS lab committee (Female section) for College of Computer and Information Sciences.

Also, during the last few years, she was able to develop her experience in university teaching by taking courses in theory and practice of university teaching, teaching courses, and attending a lot of workshops. She taught courses in Bio-informatics, Data minning, Data warehouse, data structures, discrete structures I and II, formal language theory, and algorithm analysis and design.

Date/Time: Tuesday, April 29 12-1pm

Location: Maria Auditorium, F50 in Building 6 (Broadcast to Room 2079 in CCIS Building 31)