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[nl-uiuc] AIIS talk by Prof. Heng Ji on Sept 23


Chronological Thread 
  • From: Rajhans Samdani <rsamdan2 AT illinois.edu>
  • To: nl-uiuc AT cs.uiuc.edu, aivr AT cs.uiuc.edu, vision AT cs.uiuc.edu, eyal AT cs.uiuc.edu, aiis AT cs.uiuc.edu, aistudents AT cs.uiuc.edu, "Girju, Corina R" <girju AT illinois.edu>, "Catherine Blake" <clblake AT illinois.edu>, "Efron, Miles James" <mefron AT illinois.edu>
  • Subject: [nl-uiuc] AIIS talk by Prof. Heng Ji on Sept 23
  • Date: Tue, 20 Sep 2011 14:51:52 -0500 (CDT)
  • List-archive: <http://lists.cs.uiuc.edu/pipermail/nl-uiuc>
  • List-id: Natural language research announcements <nl-uiuc.cs.uiuc.edu>

Hi all!

Details follow.

Speaker: Prof. Heng Ji (http://nlp.cs.qc.cuny.edu/hengji.html)

Time: 2 pm, Friday, Sept 23

Location: 3405, Siebel Center

Title: Leveraging Redundancy for Cross-Source Information Extraction, Fusion
and
Inference

Abstract:
One of the initial goals for Information Extraction (IE) was to create a
knowledge base
from the entire input corpus, such as a profile or a series of activities
about any entity,
and allow further logical reasoning on the knowledge base. In practice, such
information may be scattered among a variety of sources (large-scale
documents,
languages, genres and data modalities). This requires the ability to identify
topically-
related documents and to integrate facts, possibly redundant, possibly
complementary, possibly in conflict, coming from these documents.
Unfortunately the
knowledge base constructed from a typical IE pipeline often contains lots of
erroneous
and conflicting facts. Interestingly, when the data grows beyond some certain
size,
the extracted facts become inter-dependent and thus we can take advantage of
information redundancy to conduct reasoning across sources and improve the
performance of IE. This talk will describe and compare four general
frameworks to
leverange reundancy based on Information Networks to conduct more complete
information fusion and robust inference. Experiments on cross-document, cross-
lingual and cross-media IE will be presented and discussed.

Bio:
Heng Ji is an assistant professor and doctoral faculty in Computer Science at
Queens
College and the Graduate Center of City University of New York. She received
her
Ph.D. in Computer Science from New York University in 2007. Her research
interests
focus on Information Extraction and Knowledge Discovery. She was the
recipient of
NSF CAREER Award in 2010. She is the coordinator of the NIST TAC Knowledge
Base Population task in 2010 and 2011, and the IE area chair of NAACL-HLT2012.

See y'all!
Rajhans


Rajhans Samdani,
Graduate Student,
Dept. of Computer Science,
University of Illinois at Urbana-Champaign.



  • [nl-uiuc] AIIS talk by Prof. Heng Ji on Sept 23, Rajhans Samdani, 09/20/2011

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