19.2502, Calls: Computational Ling, Cog Sci/USA; Computational Ling/UK

Wed Aug 13 17:43:10 UTC 2008

LINGUIST List: Vol-19-2502. Wed Aug 13 2008. ISSN: 1068 - 4875.

Subject: 19.2502, Calls: Computational Ling, Cog Sci/USA; Computational Ling/UK

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1)
Date: 13-Aug-2008
From: Kerstin Fischer < kerstin at sitkom.sdu.dk >
Subject: Usage-based Computational Language Acquisition 

2)
Date: 12-Aug-2008
From: Udo Kruschwitz < udo at essex.ac.uk >
Subject: Corpus Profiling Workshop at IIiX 2008

-------------------------Message 1 ---------------------------------- 
Date: Wed, 13 Aug 2008 13:39:46
From: Kerstin Fischer [kerstin at sitkom.sdu.dk]
Subject: Usage-based Computational Language Acquisition
E-mail this message to a friend:
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Full Title: Usage-based Computational Language Acquisition 

Date: 28-Jul-2009 - 03-Aug-2009
Location: Berkeley, CA, USA 
Contact Person: Kerstin Fischer
Meeting Email: kerstin at sitkom.sdu.dk

Linguistic Field(s): Cognitive Science; Computational Linguistics; Language
Acquisition 

Subject Language(s): English (eng)

Call Deadline: 07-Sep-2008 

Meeting Description:

Usage-based models of language acquisition: computational perspectives
Theme Session at ICLC 11, Berkeley, CA.

Date: July 28-August 3, 2009

Organizers: Kerstin Fischer & Arne Zeschel, University of Southern Denmark 

Call for Papers

Theme Session Description:
Usage-based approaches to language acquisition have not only produced many
valuable insights in the field of child language studies (cf. Tomasello 2003 and
Goldberg 2006 for overviews), but have also helped to corroborate important
assumptions of emergentist theories of language in general (cf. Dabrowska 2005).
In line with basic tenets of Cognitive Linguistics, these approaches emphasize
the key role of communicative and experiential grounding in language use and
language structure, and seek to explain its acquisition in terms of general
(i.e., non-specialized) cognitive principles and mechanisms as far as possible.
At the same time, explicit, testable models of how these principles and
mechanisms are implemented in the context of grounded construction learning are
only beginning to be developed (cf. Bod, to appear). 

The purpose of this workshop is to bring together language acquisition
researchers from linguistics, psychology and computer science who work on such
models in order to discuss how usage-based constructionist accounts of language
acquisition can benefit from such research. Topics will include, but are not
restricted to: 

- cognitive capacities that constitute prerequisites for normal child language
acquisition (cf. Tomasello et al. 2005, Tomasello 2006) and how they can be
accommodated in language learning simulations (e.g., Steels and Kaplan 2002); 
- the basic mechanisms and psycholinguistic plausibility of different approaches
to automatic construction learning (e.g., Chang & Maia 2001; Batali 2002; Steels
2004; Dominey and Boucher 2005); 
- the kinds of semantic representations that grounded language learning
experiments or simulations should draw on (Bergen & Chang 2005; Feldman 2006); 
- the way in which the acquisition of particular constructions may be grounded
in the previous acquisition of certain other constructions (Johnson 2001;
Morris, Cottrell & Elman 2000; Abbot-Smith & Behrens 2006); and, finally,
- ways of accommodating useful notions from Cognitive Linguistics in
computational models of language processing and acquisition (cf. Chang et al.
2002). 

The session will compare different approaches to automatic construction learning
and consider the extent to which they can inform usage-based accounts of child
language acquisition. In that, it seeks to bridge the gap between kindred
research in Cognitive Linguistics and related areas of Cognitive Science, and to
provide a forum for discussing important challenges for future research on
emergentist models of language.

Submission Procedure:
Abstracts should be:
- 500 words max
- submitted in .rtf or .doc format
- turned in by Sept 7th at the latest
- accompanied by an e-mail specifying the title of the paper, name(s) of
author(s), affiliation and a contact e-mail address
- sent to kerstin at sitkom.sdu.dk and zeschel at sitkom.sdu.dk

Please note that both the theme session proposal itself and the individual
contributions will undergo independent reviewing by the ICLC program committee.

-------------------------Message 2 ---------------------------------- 
Date: Wed, 13 Aug 2008 13:39:55
From: Udo Kruschwitz [udo at essex.ac.uk]
Subject: Corpus Profiling Workshop at IIiX 2008
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http://linguistlist.org/issues/emailmessage/verification.cfm?iss=19-2502.html&submissionid=186703&topicid=3&msgnumber=2 

Full Title: Corpus Profiling Workshop at IIiX 2008 

Date: 18-Oct-2008 - 18-Oct-2008
Location: London, United Kingdom 
Contact Person: Udo Kruschwitz
Meeting Email: udo at essex.ac.uk
Web Site: http://kmi.open.ac.uk/events/corpus-profiling/index.php 

Linguistic Field(s): Computational Linguistics 

Call Deadline: 05-Sep-2008 

Meeting Description:

Corpus Profiling for Information Retrieval and Natural Language Processing
Workshop 2008 

Call for Papers (Deadline Extended):

Corpus Profiling for Information Retrieval and Natural Language Processing
Workshop 2008
18 October 2008
London
Submission deadline: Extended to 5 September 2008 
http://kmi.open.ac.uk/events/corpus-profiling/index.php

Purpose:
We aim to bring together people from different research communities interested
in exploring how corpus characteristics affect the behaviour of techniques in
information retrieval and natural language processing, and to set out a roadmap
for a shared research agenda.

It is well known in NLP and IR that the effectiveness of a technique depends on
both the data on which it is deployed and its match with the task at hand. In
1973, Spärck-Jones attributed differing degrees of success at automatic
classification to differences in dataset characteristics. Since Croft and Harper
(1979), IR performance has repeatedly been related to collection size and other
features, though no upper bound has been found.

The importance of data and task dependencies has been highlighted in IR,
anaphora resolution, automatic summarization and recently, in word sense
disambiguation. Many web/enterprise web retrieval systems rely on URL
properties, link graph properties, click streams, and so on, with performance
dependent on the degree to which this evidence is present and meaningful in a
particular corpus.

Systematically exploring features that can be used effectively to characterise
corpora, has been missing from IR/NLP research. This creates problems with
replicability of experimental results and the development of applications.

The time is right to pursue this dependence systematically to address topics in
tracking the effect of dataset profile on technique performance. Over the past
15 years, the approaches of several subject areas have converged with IR, as
large corpora and test collections assume central importance in research
methodologies. These areas have highlighted issues surrounding the role of data.

Workshop Format:
The workshop will be a day long, in conjunction with the Information Interaction
in Context (IIiX'2008, http://irsg.bcs.org/iiix2008/). The workshop will have
three components:

(1)  invited talks in the morning, introducing the background from different
perspectives
(2) two afternoon sessions, presenting peer-reviewed papers
(3) a panel discussion (panel composed of presenters and the organizers).

Topics of Interest:
We welcome original research or position papers. We particularly encourage
postgraduate students or postdoctoral researchers to submit papers. Topics of
interest include, but are not limited to, the following areas:

- Suitable features to characterise text/language variety, capturing known
effects on technique performance with respect to a task;
- Tasks that depend on aspects of corpus profiles, (e.g., the positive
correlation of QA performance with fact frequency in a corpus);
- Limitations of context-independent frequency-based measures, and exploration
of measures that highlight complex dependencies;
- Tools/techniques for characterising a feature or the extent to which it is
manifested in a corpus;
- Evaluation methodologies for testing feature candidates relative to
task/technique;
- Learnability of features (cf. meta-level learning for classification algorithms).

Important Dates:
5 September 2008: Paper submission due (Deadline Extended)
20 September 2008: Notification of acceptance/rejection
26 September 2008: Camera-ready due
18 October 2008: Workshop

Submission Guidelines:
Original technical papers, short papers and position papers are all welcome.
Please ensure that your submission does not exceed 5,000 words in length. Use 10
point font size, double column for body text, and 12 point bold for headings.
Please send your submission in PDF to all the three organizers
(A.Deroeck at open.ac.uk; d.song at open.ac.uk; udo at essex.ac.uk) with subject ''Corpus
Profiling workshop submission''.

We will publish the accepted papers electronically through BCS's Electronic
Workshops in Computing (eWiC), together with the extended abstracts of invited
talks, a summary of the panel discussion. We will seek to pursue the research
thread through further workshops at relevant conferences. We plan to organize a
post-workshop special issue on a suitable IR or NLP related journal.

Programme Committee:
Anne De Roeck (The Open University)
Udo Kruschwitz (University of Essex)
Ruslan Mitkov (University of Wolverhampton)
Nikolaos Nanas (CERETETH, Greece)
Michael Oakes (University of Sunderland)
Ian Ruthven (University of Strathclyde)
Dawei Song (KMi, The Open University)
Tomek Strzalkowski (SUNY Albany)
Alistair Willis (The Open University)

For further information please visit
http://kmi.open.ac.uk/events/corpus-profiling/index.php

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