题目：Simultaneous Pattern and Data Clustering for Discrete-Valued Data
报告人：Dr. Andrew K.C. Wong IEEE Fellow , University of Waterloo, Canada
时间：3月26日（星期一），14:30-15:30
地点：蒙民伟楼404会议室
Abs:
In data mining and knowledge discovery, pattern discovery is developed
to discover previously unknown regularities in the data. However, the number
of patterns produced by pattern discovery is usually overwhelming. To effectively
manage the discovered patterns for further analysis from a large database,
where interesting information and relevant patterns might be scattered,
entangled and spanning in various data subspaces, is still a great challenge.
This talk will present a new method to simultaneously cluster patterns
and data to meet this challenge. It is different from conventional clustering
in which the relation between the clustered data and the clustered patterns
is established explicitly. This explicit data-pattern relation serves two
purposes: data analysis and human interpretation. While data is grouped
and broken down for further analysis, patterns are easy for human to interpret.
The data-pattern relation enables users, on the one hand, to further analyze
individual clusters and their relations via the data, and, on the other,
to interpret why the data clusters are formed through the patterns they
contain. Furthermore, within each cluster, noises are marginalized and
irrelevant peripheral data are filtered out. Hence, the data can be analyzed
more effectively. To achieve in-depth data analysis, the proposed method
takes a divide-and-conquer approach. A large set of patterns is first clustered
and each pattern cluster together with its associated data grouping is
studied individually as supported by the explicit data-pattern relation.
To evaluate the characteristics and the effectiveness of the proposed method,
extensive experimental results on synthetic and real-world data are presented.
Comparisons with other related methods are also given.
Bio:
Dr. Andrew K.C. Wong currently is a Distinguished Professor Emeritus at
the University of Waterloo where he is also an Adjunct Professor of the
School of Computer Sciences and the Electrical and Computer Engineering
Department. He was the Founding Director of the renowned Pattern Analysis
and Machine Intelligence Laboratory (PAMI Lab) and a Distinguished Chair
Professor at the Hong Kong Polytechnic University (00-03). Dr. Wong holds
a Ph.D. from Carnegie Mellon University; and a B.Sc (Hons) and M.Sc. from
the Hong Kong University. He is an IEEE Fellow (for his contribution in
machine intelligence, computer vision, and intelligent robotics). |
