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Seminars on Selected Topics in Database Research

Speaker: Dr. Wang Haixun, IBM T. J. Watson Research Center

Abstract
The database area is experiencing a vigorous and often tumultuous growth as 
a result of a push by new technology combined with a pull by new 
applications. The goal of this seminar series is to provide a broad exposure 
to the research being done in this area.  The series will include such 
topics as database indexing, XML, data mining, database language, and the 
stream DBMS. I will present, for each topic, a brief survey, some specific 
research issues and their tentative solutions. The series is also aimed at 
inspiring students to engage in original research in this active area. 

Seminars 1: Indexing Techniques for Advanced Database Applications 

Time: 8:30-11:30am, Dec 2, 2003    Classroom:  4302#

Indexing is one of the most fundamental and extensively studied topics in 
the database field. In this talk, I will introduce a certain class of 
database query that is not well supported by current indexing techniques. 
However, efficient handling of such queries are essential to a wide range of 
database applications, including those in system management, bioinformatics, 
XML information systems, etc. To serve these applications, I present the 
sequence data model as well as an index structure designed specifically for 
the data model. I will show how data in different forms, including 
sequential, relational, and semi-structured, can be mapped nicely into this 
data model, and how queries over those different data are efficiently 
supported by the index structure.

Seminars 2: Clustering, Classification, and other Data Mining Techniques 

Time: 2:00-:4:30pm, Dec 3, 2003    Classroom:  4505#

Data mining is a research area spanning several disciplines, including 
database systems, machine learning, statistics, etc.  For instance, 
clustering and classification, which are among the core techniques of data 
mining, have been studied extensively in machine learning. Nevertheless, new 
applications, especially data-intensive applications, have constantly 
introduced practical and theoretical challenges to these techniques. As our 
first example, I will show applications in E-commerce, bioinformatics that 
require new distance models to measure pattern similarity. This opens up 
many new research issues to clustering. As a second example, we study 
classification in
the new environment of streaming data that has time-changing distributions. 
I will present and compare several different solutions to these challenges. 

Seminars 3: Advanced Topics in Database Language and Systems

Time: 8:30-11:30am, Dec 4, 2003    Classroom:  4605#

A lack of power and extensibility in their query languages has seriously 
limited the generality of DBMSs and hampered their ability to support new 
applications domains. Considerable efforts by database researchers and 
commercial DBMS vendors were devoted at overcoming these limitations, and 
led to the introduction in commercial DBMSs of significant extensions, 
including those for ROLAPs, recursive queries, and datablades. However, the 
effectiveness of these extensions is restricted to specific application 
domains, and there remain important applications are not supported well in 
SQL3. Thus, there is a pressing need for more general mechanisms for 
extending SQL and dealing with new application areas. In this talk, I will 
present the ATLaS system, which answers this need by means of generalized 
table functions and aggregate functions defined using the SQL language 
itself, rather than an external programming language. This simple extension 
turns SQL into a powerful database language, which can express a wide range 
of applications, including recursive queries, ROLAP aggregates, time series 
queries, and data mining functions. In addition to bringing great power and 
flexibility to SQL, the ATLaS system achieves excellent performance..

Biography
Haixun Wang is currently a research staff member at IBM T. J. Watson 
Research Center. He received the B.S. and the M.S. degree, both in computer 
science, from Shanghai Jiao Tong University in 1994 and 1996. He received 
the Ph.D. degree in computer science from the University of California, Los 
Angeles in 2000. He has published more than 40 research papers in referred 
international journals and conference proceedings (VLDB, SIGMOD, ICDE, 
etc.). He is a member of the ACM, the ACM SIGMOD, the ACM SIGKDD, and the 
IEEE Computer Society. He has served in program committees of international 
conferences and workshops, and has been a reviewer for some leading academic 
journals in the database field.





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