Apologies for multiple copies
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*** C A L L F O R P A P E R S ***
WORKSHOP ON ADAPTIVE TEXT EXTRACTION AND MINING (ATEM03)
(plus introductory TUTORIAL)
at the joint 14th European Conference on Machine Learning (ECML)
and 7th European Conference on Principles and Practice of Knowledge
Discovery in Databases (PKDD)
Monday 22 September 2003 [tentative]
Cavtat-Dubrovnik (Croatia)
Important facts:
- submission due: 20 June 2003 **************EXTENDED DEADLINE*************
- Web page: www.dcs.shef.ac.uk/~fabio/ATEM03
MOTIVATION
-----------------
Vast quantities of valuable knowledge are embedded in unstructured
textual formats. Petabytes of text are currently available on the
public Web, in intranets and other private repositories, and on our
personal desktop machines. In many cases, the only way to access such
documents is through blunt instruments such as keyword-based document
retrieval. In recent years, there has been significant research (and
considerable commercial interest) in technologies for automatically
extracting and mining useful structured knowledge from unstructured
text. Current trends suggest a movement away from pure natural
language processing approaches requiring the manual development of
rules, to a shallower, less knowledge intensive techniques based on
techniques from machine learning, information retrieval and data
mining.
Adaptive text extraction and mining is an enabling technology with a
wide variety of applications. On the Web, automated knowledge capture
from text would open the way for both better retrieval, and advanced
business applications (e.g. B2B/B2C applications mediated by
knowledge-aware agents). For knowledge management, capturing the
knowledge contained in a companys repositories would encourage
knowledge to be shares and reused among employees, improving
efficiency and competitiveness. Extracting information from texts is
an important step in capturing knowledge, e.g. for populating
databases or ontologies, supporting document annotation (e.g. for the
Semantic Web), for learning ontologies, etc.
THE WORKSHOP
---------------------
The workshop will bring together researchers and
practitioners from different communities (e.g. machine learning, text
mining, natural language processing, information extraction,
information retrieval, ontology learning) to discuss recent results
and trends in mining texts for knowledge capture. Members of other
communities (e.g. information integration and data mining) could find
the workshop very interesting as well. Previous workshops on the use
of machine learning for information extraction were held at AAAI-1998,
ECAI-2000, and IJCAI-2001.
AREAS OF INTEREST.
------------------
Areas of interest for the workshop include (but
are not limited to):
* machine learning and natural language
* learning to annotate documents
* ontology learning
* information retrieval and learning
* information integration from textual and multimedia resources
* relevant aspects of human-computer interaction and semi-supervised
learning
SUBMISSION DETAILS
------------------
ATEM-2003 will accept two types of submissions:
long papers that describe completed research (maximum 8 pages); and
short papers that describe ongoing work or challenging ideas (maximum
4 pages).
Proceeding of the workshop will be produced.
The most interesting papers presented at the workshop will
be considered for a special issue of a scientific journal.
Manuscripts should be formatted for A4 paper, and must be submitted in
either PDF or Postscript format. Send submissions to
"f.ciravegna@dcs.shef.ac.uk" with subject "ATEM submission".
IMPORTANT DATES
Please note the following deadlines:
- Paper submission deadline: Friday 20 June 2003 ***extended deadline ***
- Paper acceptance notification: Friday 4 July 2003
- Paper camera-ready deadline: Friday 11 July 2003
- Workshop date: Monday 22 September 2003 [tentative]
JOINT TUTORIAL
--------------
Researchers who are interested but not yet involved
in adaptive text extraction and mining are encouraged to attend the
tutorial "Information Extraction from Web Documents" at ECML-2003.
This introductory tutorial has been organized by the workshop chairs
to complement the research focus of ATEM-2003.
SPONSORSHIP
-----------
The workshop will be partly funded by a grant from the European Project
"dot.kom".
ORGANIZERS
----------
* Fabio Ciravegna (University of Sheffield) [co-chair]
f.ciravegna@dcs.shef.ac.uk (contact point)
* Nicholas Kushmerick (University College Dublin) [co-chair] nick@ucd.ie
PROGRAMME COMMITTE
------------------
* Valter Crecenzi (Universite Roma Tre)
* Dayne Freitag (Fair, Isaac and Company)
* Ion Muslea (University of California, Irvine)
* Hwee Tou Ng (National University of Singapore)
* Mark Stevenson (University of Sheffield)
* Roman Yangarber (New York University)
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