CFP: Active Learning for NLP Workshop at NAACL-HLT
Burr Settles
Second Call for Paper Submissions
NAACL-HLT 2010 Workshop on
Active Learning for Natural Language Processing (ALNLP)
June 5 or 6, 2010, Los Angeles, CA
http://www.active-learning.net/alnlp2010
Submission Deadline: March 1, 2010
==============================================================
Labeled training data is required to achieve state-of-the-art
performance for
many machine learning solutions to NLP tasks. While traditional
supervised
methods relies exclusively on existing labeled data to induce a model,
active
learning allows the learner to select unlabeled data for labeling in
an effort to
reduce annotation costs without sacrificing performance. Thus, active
learning
appears promising for NLP applications where unlabeled data is
readily
available (e.g., web pages, audio recordings, minority language data),
but
obtaining labels is cost-prohibitive.
Ample recent work has demonstrated the effectiveness of active
learning over
a diverse range of applications. Despite these findings, active
learning has
not yet been widely adopted for many ongoing large-scale corpora
annotation
efforts -- resulting in a dearth of real-world case studies and
copious research
questions. Machine learning literature has primarily focused on
active learning
in the context of classification, devoting less attention to issues
specific to NLP
including annotation user studies, incorporation of semantic
information, and
more complex prediction tasks (e.g. parsing, machine translation).
TOPICS
The aim of this workshop is to foster innovation and discussion that
advances
our understanding in these and other practical issues for active
learning in NLP.
Topics of particular interest include:
-- Alternative query types: labeling features rather than
instances,
mixed-resolution queries for structured instances, etc.
-- Creative ways for obtaining data via active learning (e.g.,
online games,
Mechanical Turk)
-- Managing multiple, possibly non-expert annotators (e.g.,
"crowdsourcing"
environments)
-- Reusability: using data acquired with one active learner to train
other
model classes
-- Domain adaptation and active learning
-- Multi‐task active learning
-- Criteria for stopping and monitoring active learning progress
-- Active learning in coordination with semi-supervised or
unsupervised
learning approaches
-- Interactive active learning interfaces and other HCI issues
-- Parallelization of active learning and its computational
challenges
-- Software engineering considerations for active learning and NLP
-- Theoretical analysis of active learning
We also welcome case-study papers describing the application of
active
learning in real-world annotation projects and lessons learned
thereby.
Additionally, we would consider papers with insights applicable to NLP
from
other machine learning communities (e.g., computer vision,
bioinformatics,
and data mining), where annotation costs are also high.
SUBMISSIONS
We invite submissions of two kinds: 1. original and unpublished work
as
full papers, limited to 8 pages (+1 extra page for references); 2.
position or
work-in-progress papers, limited to 4 pages (including references).
Both kinds
of papers will appear in the proceedings and presented orally. As
reviewing
will be double-blind, author information should not be included in the
papers
and self-reference should be avoided.
All submissions must be made in PDF format using the START paper
submission website:
https://www.softconf.com/naaclhlt2010/alnlp/
Submissions must follow the NAACL HLT 2010 formatting requirements:
http://naaclhlt2010.isi.edu/authors.html
Authors are strongly encouraged to use the LaTeX or Microsoft Word
style
files available there. Papers not conforming to these requirements
are
subject to rejection without review.
IMPORTANT DATES
March 1, 2010: Paper Submission Deadline
March 30, 2010: Notification of acceptance
June 5 or 6, 2010: Workshop held in conjunction with NAACL-HLT
ORGANIZERS AND CONTACT
- Burr Settles, Carnegie Mellon University, USA
- Kevin Small, Tufts University, USA
- Katrin Tomanek, University of Jena, Germany
Please address any queries regarding the workshop to:
alnl...@gmail.com
PROGRAM COMMITTEE
- Markus Becker (SPSS, UK)
- Claire Cardie (Cornell University, USA)
- Hal Daume III (University of Utah, USA)
- Ben Hachey (University of Edinburgh, UK)
- Robbie Haertel (Brigham Young University, USA)
- Udo Hahn (University of Jena, Germany)
- Eric Horvitz (Microsoft Research, USA)
- Rebecca Hwa (University of Pittsburgh, USA)
- Ashish Kapoor (Microsoft Research, USA)
- Prem Melville (IBM T.J. Watson Research Center, USA)
- Ray Mooney (University of Texas at Austin, USA)
- Fredrik Olsson (SICS, Sweden)
- Foster Provost (New York University, USA)
- Eric Ringger (Brigham Young University, USA)
- Dan Roth (University of Illinois at Urbana-Champaign, USA)
- Burr Settles (Carnegie Mellon University, USA)
- Kevin Small (Tufts University, USA)
- Katrin Tomanek (University of Jena, Germany)
Markus Becker
Could you please update my affiliation to Markus Becker (SPSS, an IBM company)? Likewise, the affiliation of Ben Hachey needs updating. (We had an email exchange about this in December.)
Thanks a lot,
Markus Becker
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