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LINGUIST List 20.4442

Mon Dec 21 2009

Calls: Computational Ling/India

Editor for this issue: Kate Wu <katelinguistlist.org>

LINGUIST is pleased to announce the launch of an exciting new feature: Easy Abstracts! Easy Abs is a free abstract submission and review facility designed to help conference organizers and reviewers accept and process abstracts online. Just go to: http://www.linguistlist.org/confcustom, and begin your conference customization process today! With Easy Abstracts, submission and review will be as easy as 1-2-3!
        1.    Richa Srishti, Knowledge Sharing Event-4- POS Tagging

Message 1: Knowledge Sharing Event-4- POS Tagging
Date: 21-Dec-2009
From: Richa Srishti <ldc-richaciil.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: rsrishtigmail.com or ldc-richaciil.stpmy.soft.net
Web Site: http://www.ldcil.org/up/pos.html

Linguistic Field(s): Computational Linguistics

Call Deadline: 15-Jan-2010

Meeting Description:

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 language.

The POS tagging is not about just providing a tag to a token but it encompasses
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, parsing, machine
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 translation.
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, though more
accurate, is a time-consuming, long and continuous process. Hence, the automatic
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 POS tagging
and to share and investigate novel advancements in the area specific to a
language as well as cross-linguistically. It also aims to provide researchers an
academic space to discuss the most recent information about theories, tools and
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 the title
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
email address:
rsrishtigmail.com or ldc-richaciil.stpmy.soft.net
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