Fwd: 20.4442, Calls: Computational Ling/India
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----- Weitergeleitete Nachricht von linguist at LINGUISTLIST.ORG -----
Datum: Mon, 21 Dec 2009 11:55:05 -0500
Von: linguist at LINGUISTLIST.ORG
Antwort an: linguist at LINGUISTLIST.ORG
Betreff: 20.4442, Calls: Computational Ling/India
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LINGUIST List: Vol-20-4442. Mon Dec 21 2009. ISSN: 1068 - 4875.
Subject: 20.4442, Calls: Computational Ling/India
From: Richa Srishti < ldc-richa at ciil.stpmy.soft.net >
Subject: Knowledge Sharing Event-4- POS Tagging
-------------------------Message 1 ----------------------------------
Date: Mon, 21 Dec 2009 11:52:54
From: Richa Srishti [ldc-richa at ciil.stpmy.soft.net]
Subject: Knowledge Sharing Event-4- POS Tagging
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Full Title: Knowledge Sharing Event-4- POS Tagging
Short Title: KSE-4-POST
Date: 25-Mar-2010 - 26-Mar-2010
Location: Mysore, Karnataka, India
Contact Person: Richa Srishti
Meeting Email: rsrishti at gmail.com or ldc-richa at ciil.stpmy.soft.net
Web Site: http://www.ldcil.org/up/pos.html
Linguistic Field(s): Computational Linguistics
Call Deadline: 15-Jan-2010
The LDC-IL, is organising a series of events to bring together researchers
working in these areas, to share their knowledge with other researchers.
Call for Papers
The following changes have been made regarding the conference:
1. Abstract submission date: 15-Jan-2010.
3. Abstract acceptance notification: 30-Jan-2010.
4. Full length paper: 20-Feb-2010.
Each of the events in the series will focus on one aspect of computational
grammar at a time and thereby address issues related to these themes.
Parts-of-speech (POS) tagging is the basic building block of any NLP work,
hence, the first step in developing the computational grammar for any
The POS tagging is not about just providing a tag to a token but it
a whole range of grammatical information for that token in the sentence from a
particular language. Besides, designing the tagset for a specific NLP purpose,
preparing annotation guidelines and interannotator agreement are also very
important. It is an active research area in NLP.
POS tagging is useful in speech generation, speech recognition,
translation, information retrieval, information extraction, WSD (word sense
disambiguation), question-answering etc. Moreover, it is an intermediate step
for higher NLP tasks such as parsing, semantic analysis and machine
Especially regarding Indian languages, POS tagging adds many more dimensions,
involving many complex issues that arise out of script, writing convention
specific to the language, inherent POS ambiguities as well as with respect to
unknown tokens and variations in the text.
POS tagging can be both manual as well as automatic. Manual tagging,
accurate, is a time-consuming, long and continuous process. Hence, the
tagger is essential to speed up the process of POS tagging with less chance of
errors and inconsistencies. Various automatic POS taggers have been developed
worldwide using linguistic rules, stochastic models and hybrid taggers (a
combination of both). Different kinds of taggers have certain
advantages as well
as disadvantages. Automatic tagging is a challenge for Indian languages which
are highly inflectional and morphologically rich. Hence, the
development of high
accuracy POS taggers is a challenging task.
The event endeavours to concentrate on the challenges in the area of
and to share and investigate novel advancements in the area specific to a
language as well as cross-linguistically. It also aims to provide
academic space to discuss the most recent information about theories,
techniques explored for POS tagging, and focuses on linguistic as well as
computational issues related to it. The event intends to endorse the
area of POS
tagging as a consolidated research area and aims towards widening its horizon.
Abstracts of no more than 500 words (including references) mentioning
of the paper, author(s) name, institutional affiliation, and email address
should be submitted by the due date in *.rtf or *.pdf format to the following
rsrishti at gmail.com or ldc-richa at ciil.stpmy.soft.net
LINGUIST List: Vol-20-4442
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