Shallow Integration over the Deep Web

Over the past few years, the Web has deepened dramatically- A
significant amount of information is hidden on the "deep" Web, behind
the query interfaces of searchable databases. There are numerous such
autonomous and heterogeneous sources, each with a different schema and
query capabilities. Our MetaQuerier project, the context of this talk,
aims to build a "metaquery" system, to help users in both finding
and querying online databases effectively.

While the sheer scale of the deep Web poses a real challenge for
information integration, we believe the challenge is itself a unique
opportunity-- We propose to tackle the "deep" semantics by exploring
"shallow" syntax and statistics hidden across the large scale: 1)
Observations: To motivate, I will briefly report our Dec. 2002 survey
of this new frontier (How many sources? How are they covered by search
engines?  How "complex" are they? etc.), which reveals some inspiring
"concerted complexity" phenomena. 2) Implications: I will contend our
general view of shallow integration. 3) Evidences: I will demonstrate
by two specific works, namely query-interface understanding (by
syntactic hidden-grammar parsing), and schema matching (by statistic
hidden-hypothesis discovery).

Project URL: http://metaquerier.cs.uiuc.edu

Bio:

Kevin Chen-Chuan Chang is an Assistant Professor in Computer Science,
University of Illinois at Urbana-Champaign. He received a PhD in
Electrical Engineering in 2001 from Stanford University. His research
interests are in large-scale information access, with emphasis on
information integration and top-k ranked query processing. He is the
recipient of an NSF CAREER Award in 2002 and an NCSA Faculty Fellow in
2003.  URL: http://www-faculty.cs.uiuc.edu/~kcchang