19.3793, Calls: Computational Ling/USA; General Ling/USA

[LINGUIST Network]

LINGUIST List: Vol-19-3793. Thu Dec 11 2008. ISSN: 1068 - 4875.

Subject: 19.3793, Calls: Computational Ling/USA; General Ling/USA

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===========================Directory==============================  

1)
Date: 11-Dec-2008
From: Eric Ringger < ringger at cs.byu.edu >
Subject: NAACL HLT 2009 Workshop on Active Learning for NLP 

2)
Date: 10-Dec-2008
From: Cassandra Pace < cjp2 at rice.edu >
Subject: The Biennial Meeting of the Rice Linguistics Society

 

	
-------------------------Message 1 ---------------------------------- 
Date: Thu, 11 Dec 2008 09:29:00
From: Eric Ringger [ringger at cs.byu.edu]
Subject: NAACL HLT 2009 Workshop on Active Learning for NLP  	 

E-mail this message to a friend:
http://linguistlist.org/issues/emailmessage/verification.cfm?iss=19-3793.html&submissionid=199226&topicid=3&msgnumber=1
  

Full Title: NAACL HLT 2009 Workshop on Active Learning for NLP 
Short Title: ALNLP 

Date: 05-Jun-2009 - 05-Jun-2009
Location: Boulder, Colorado, USA 
Contact Person: Eric Ringger
Meeting Email: ringger at cs.byu.edu
Web Site: http://nlp.cs.byu.edu/alnlp/ 

Linguistic Field(s): Computational Linguistics 

Call Deadline: 06-Mar-2009 

Meeting Description:

The Workshop on Active Learning for Natural Language Processing will explore the
challenges and promise of active learning for NLP tasks, including
classification, sequence labeling, parsing, semantics, and other more complex
tasks.  Both theoretical and applied research is welcome. 

Call for Papers

NAACL HLT 2009 Workshop on
Active Learning for Natural Language Processing
June 5, 2009, Boulder, Colorado, USA
http://nlp.cs.byu.edu/alnlp/

Submission Deadline: March 6, 2009

Endorsed by the following ACL Special Interest Group:
SIGANN, Special Interest Group for Annotation

Motivation
Labeled data is a prerequisite for many popular algorithms in natural language
processing and machine learning.  While it is possible to obtain large amounts
of annotated data for well-studied languages in well-studied domains and well-
studied problems, labeled data are rarely available for less common languages,
domains, or problems.  Unfortunately, obtaining human annotations for linguistic
data is labor-intensive and typically the costliest part of the acquisition of
an annotated corpus.

It has been shown before that active learning can be employed to reduce
annotation costs but not at the expense of quality.  While diverse work over the
past decade has demonstrated the possible advantages of active learning for
corpus annotation and NLP applications, active learning is not widely used in
many ongoing data annotation tasks.  Much of the machine learning literature on
the topic has focused on active learning for classification problems with less
attention devoted to the kinds of problems encountered in NLP.

Topics
We are interested in bringing together researchers in this area to explore the
challenges of active learning for NLP tasks.  General work on active learning on
NLP classification tasks, sequence labeling, parsing, semantics, and other more
complex tasks will be welcome in the workshop.  More specific topics of interest
include, but are not limited to:
- theoretical analysis of active learning in the context of NLP applications
- novel active learning approaches to estimate the training utility of
individual selection units
- cost-sensitive active learning approaches incorporating data acquisition costs
- approaches to model or predict annotation costs as well as studies on factors
that influence annotation time
- criteria for stopping or monitoring progress of active learning
- overfitting of data acquired with active learning: how much is the data biased
towards the learning scheme involved in the selection and what are the
limitations of re-use with other learning schemes
- Human-Computer Interaction aspects of annotation including requirements,
impact of interface design on annotation time, and methods to deal with
reliability of annotators
- approaches to multi-task active learning
- approaches to deal with or reduce computational complexity of active learning
approaches including parallelization, issues of pool- or batch-size, varying
degrees of look-ahead, etc.
- active learning and domain adaption
- active learning compared to or combined with other semi-supervised or even
unsupervised learning approaches
- application of active learning in real annotation projects and experiences
gained thereby

Submissions
We invite submissions of two kinds:  1. original and unpublished work as full
papers, limited to 8 pages; 2. position papers or papers describing ongoing work
as short papers, limited to 4 pages.  Both kinds of papers will appear in the
proceedings and will be 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/naacl-hlt09/ActiveLearningNLP2009/
Submissions must follow the NAACL HLT 2009 formatting requirements:
http://clear.colorado.edu/NAACLHLT2009/stylefiles.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 6, 2009: Submission Deadline
March 30, 2009: Notification of acceptance
April 12, 2009: Camera-ready copies due
June 5, 2009: Workshop held in conjunctions with NAACL HLT

Organizers and Contact
- Eric Ringger, Brigham Young University, USA
- Robbie Haertel, Brigham Young University, USA
- Katrin Tomanek, University of Jena, Germany

Please address any queries regarding the workshop to:
al.nlp2009 at googlemail.com

Program Committee
- Shlomo Argamon (Illinois Institute of Technology, USA)
- Jason Baldridge (University of Texas at Austin, USA)
- Markus Becker (SPSS, UK)
- Ken Church (Microsoft Research, USA)
- Hal Daume (University of Utah, USA)
- Robbie Haertel (Brigham Young University, USA)
- Ben Hachey (University of Edinburgh, UK)
- Udo Hahn (University of Jena, Germany)
- Eric Horvitz (Microsoft Research, USA)
- Rebecca Hwa (University of Pittsburgh, USA)
- Ashish Kapoor (Microsoft Research, USA)
- Mark Liberman (University of Pennsylvania/LDC, USA)
- Prem Melville (IBM T.J. Watson Research Center, USA)
- Ray Mooney (University of Texas at Austin, USA)
- Miles Osborne (University of Edinburgh, UK)
- Eric Ringger (Brigham Young University, USA)
- Kevin Seppi (Brigham Young University, USA)
- Burr Settles (University of Wisconsin, USA)
- Victor Sheng (New York University, USA)
- Katrin Tomanek (University of Jena, Germany)
- Jingbo Zhu (Northeastern University, China)



	
-------------------------Message 2 ---------------------------------- 
Date: Thu, 11 Dec 2008 09:29:10
From: Cassandra Pace [cjp2 at rice.edu]
Subject: The Biennial Meeting of the Rice Linguistics Society

E-mail this message to a friend:
http://linguistlist.org/issues/emailmessage/verification.cfm?iss=19-3793.html&submissionid=199191&topicid=3&msgnumber=2
 
	

Full Title: The Biennial Meeting of the Rice Linguistics Society 

Date: 21-Feb-2009 - 22-Feb-2009
Location: Houston Texas, USA 
Contact Person: Cassandra Pace
Meeting Email: rls at rice.edu
Web Site: http://www.ruf.rice.edu/~rls/ 

Linguistic Field(s): General Linguistics 

Call Deadline: 05-Jan-2009 

Meeting Description:

The Rice Linguistics Society is pleased to announce its 3rd Biennial Meeting in
Houston Texas February 21-22, 2009. 

Call for Papers

The Rice Linguistics Society would like to announce an extension of their call
for abstract submissions for its Biennial Meeting.  We are now accepting paper
proposals through January 5th, 2009.


 





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