Natural language research announcements

[Julia Hockenmaier <juliahmr AT cs.uiuc.edu>]

There won't be an NLP lunch today, but please come to Andrew  
McCallum's talk today at 3:30!



   Information Extraction, Data Mining and Joint Inference
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                Andrew McCallum
   University of Massachusetts Amherst

               Tuesday, April 7, 3:30pm
              Siebel Center Room 1404


Abstract: Although information extraction and data mining appear
together in many applications, their interface in most current systems
could be better described as serial juxtaposition rather than as tight
integration.  Information extraction populates slots in a database by
identifying relevant subsequences of text, but is usually not aware of
the emerging patterns and regularities in the database.  Data mining
methods begin from a populated database, and are often unaware of
where the data came from, or its inherent uncertainties.  As a result
the accuracy of both suffers, and accurate mining of complex text
sources has been beyond reach.

In this talk, Dr. McCallum will describe work in probabilistic models
that perform joint inference across multiple components of an
information processing pipeline in order to avoid the brittle
accumulation of errors.  The need for joint inference appears not only
in extraction and data mining, but also in natural language
processing, computer vision, robotics and elsewhere.  He will argue
that joint inference is one of the most fundamental issues in
artificial intelligence.

Dr. McCallum will present recent work in conditional random fields for
information extraction and integration, with a focus on joint
inference through stochastic approximations, weighted first-order
logic, and new methods of probabilistic programming that enable
reasoning about large-scale data.  He will close with a demonstration
of Rexa.info, a digital research library that leverages these
techniques.

Biographical: Andrew McCallum is an Associate Professor and Director
of the Information Extraction and Synthesis Laboratory in the Computer
Science Department at University of Massachusetts, Amherst.  He has
published over 100 papers in many areas of AI, including natural
language processing, machine learning, data mining and reinforcement
learning, and his work has received over 13,000 citations.  He
received his PhD from University of Rochester in 1995 with Dana
Ballard and a postdoctoral fellowship from CMU with Tom Mitchell and
Sebastian Thrun.  Afterward he worked in an industrial research lab,
where he spearheaded the creation of CORA, an early search engine that
used machine learning for spidering, extraction, classification and
citation analysis.  In the early 2000's he was Vice President of
Research and Development at WhizBang Labs, a 170-person start-up
company that used machine learning for information extraction from the
Web.  He was the Program Co-chair for the International Conference on
Machine Learning (ICML) 2008, and a member of the boards of the
International Machine Learning Society, the CRA Community Computing
Consortium and the editorial board of the Journal of Machine Learning
Research.  For the past ten years, McCallum has been active in
research on statistical machine learning applied to text, especially
information extraction, co-reference, document classification,
clustering, finite state models, semi-supervised learning, and social
network analysis.

For more information: Work on search and bibliometric analysis of open-
access research literature can be found at http://rexa.info.  Andrew
McCallum's web page ishttp://www.cs.umass.edu/~mccallum.

Collaborators: Charles Sutton, Aron Culotta, Khashayar Rohanemanesh,
Chris Pal, Greg Druck, Karl Schultz, Sameer Singh, Pallika Kanani,
Kedare Bellare, Michael Wick, Rob Hall, David Mimno and Gideon Mann.
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     Julia Hockenmaier
     Department of Computer Science, University of Illinois
     3324 Siebel Center, 201 N Goodwin Ave
     Urbana, IL 61801-2302, USA
     Tel: +1 (217) 265-6855    Fax: +1 (217) 265-6591
     http://www.cs.uiuc.edu/~juliahmr
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