Difference between revisions of "Event:B5691926-e33e-48aa-8066-2c39832e75e8"

From ConfIDent
(mobo import Concept___Events-migrated)
(mobo import Fix Deadline Migration Bug-migrated)
Tag: Replaced
Line 1: Line 1:
 
{{Event
 
{{Event
|Acronym=Corpus Profiling 2008
+
|Title=2. Fachkonferenz Kinder- und Jugendbibliotheken
|Title=Corpus Profiling for Information Retrieval and Natural Language Processing Workshop
+
|Ordinal=2
|Type=Workshop
+
|In Event Series=Event Series:Dbc7071a-aa41-495a-8e00-29efb6b47934
|Homepage=kmi.open.ac.uk/events/corpus-profiling/index.php
 
|City=London
 
|Country=Country:GB
 
|wikicfpId=3474
 
|pageCreator=127.0.0.1
 
|contributionType=1
 
 
|Single Day Event=no
 
|Single Day Event=no
|Start Date=Oct 18, 2008
+
|Start Date=2017/02/15
|End Date=Oct 18, 2008
+
|End Date=2017/02/18
|Academic Field=Information Retrieval
 
 
|Event Status=as scheduled
 
|Event Status=as scheduled
 
|Event Mode=on site
 
|Event Mode=on site
}}
+
|City=Remscheid
{{Event Deadline
+
|Region=Nordrhein-Westfalen
|Notification Deadline=Sep 12, 2008
+
|Country=Country:DE
|Camera-Ready Deadline=Sep 26, 2008
 
|Submission Deadline=Aug 15, 2008
 
 
}}
 
}}
 
{{Event Deadline}}
 
{{Event Deadline}}
 
{{S Event}}
 
{{S Event}}
 
<pre>
 
-----------------------------------
 
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
 
-----------------------------------
 
 
15 August 2008: Paper submission due
 
 
12 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@open.ac.uk; d.song@open.ac.uk;
 
udo@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
 
</pre>This CfP was obtained from [http://www.wikicfp.com/cfp/servlet/event.showcfp?eventid=3474&amp;copyownerid=2 WikiCFP][[Category:Natural language processing]]
 
[[Category:Information retrieval]]
 

Revision as of 12:49, 28 September 2022

Deadlines
Venue

Remscheid, Nordrhein-Westfalen, Germany

Loading map...
Cookies help us deliver our services. By using our services, you agree to our use of cookies.