* * * * * * * * * * * * * * * * * * * * * * * *
LINGUIST List logo Eastern Michigan University Wayne State University *
* People & Organizations * Jobs * Calls & Conferences * Publications * Language Resources * Text & Computer Tools * Teaching & Learning * Mailing Lists * Search *
* *
LINGUIST List 22.2329

Thu Jun 02 2011

Calls: Computational Linguistics, Text/Corpus Linguistics/China

Editor for this issue: Alison Zaharee <alisonlinguistlist.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.     Christoph Ringlstetter , 5th Workshop on Analytics for Noisy Unstructured Text

Message 1: 5th Workshop on Analytics for Noisy Unstructured Text
Date: 01-Jun-2011
From: Christoph Ringlstetter <kristofcis.uni-muenchen.de>
Subject: 5th Workshop on Analytics for Noisy Unstructured Text
E-mail this message to a friend

Full Title: 5th Workshop on Analytics for Noisy Unstructured Text
Short Title: AND2011

Date: 17-Sep-2011 - 17-Sep-2011
Location: Beijing, China
Contact Person: Christoph Ringlstetter
Meeting Email: < click here to access email >
Web Site: http://and2011.cse.lehigh.edu/

Linguistic Field(s): Computational Linguistics; Text/Corpus Linguistics

Call Deadline: 14-Jun-2011

Meeting Description:

5th Workshop on Analytics for Noisy Unstructured Text Data

In conjunction with ICDAR 2011
September 17th, 2011, Beijing, China

Noisy unstructured text data is ubiquitous in real-world communication.
Natural language and the creative ways that humans use it can create
problems for computational techniques. Electronic text from the Internet
(emails, message boards, newsgroups, blogs, wikis, chatlogs and web pages),
contact centers (complaints, emails, call transcriptions, message
summaries), and mobile phones (SMS) is often noisy - contains spelling
errors, abbreviations, non-standard words, false starts, repetitions,
missing punctuation, missing case information and special characters.

Informal communications are not the only source of noisy text; text
produced by processing signals intended for human use such as
printed/handwritten documents, spontaneous speech, and camera-captured
scene images, are prime examples. Recognition errors made by Optical
Character Recognition (OCR) and Automatic Speech Recognition (ASR) systems
can result in imperfect transcriptions. An increasing stream of imperfect
OCR results are featured by ongoing mass-digitization of the world's
written cultural heritage. Such noise in text has raised new sets of
challenges for the task of Information Retrieval and Knowledge Management.
Special handling of noise as well as noise robust IR and KM techniques are
essential to overcome those challenges.

AND 2011 is a workshop devoted to issues arising from the need to contend
with noisy inputs, the impact noise can have on downstream applications,
and the demands it places on document analysis.

Call for Papers:

Important Dates:

Abstract Submission: June 7th, 2011
Paper Submission: June 14th, 2011
Notification of Acceptance: July 25th, 2011
Camera-Ready papers due: August 8th, 2011

We welcome original research papers that identify key problems related to
noisy text analytics and offer solutions. Potential topics include (but not
limited to):

- Noise induced by document analysis techniques and its impact on
downstream applications
- Formal theory on characterization of noise
- Genre recognition based on the type of noise
- Robust parsing and Part of Speech (POS) tagging
- Characterizing, modelling and accounting for historical language change
- Methods for detecting and correcting errors in noisy text
- Information extraction and retrieval from noisy text data
- Automatic classification and clustering of noisy unstructured text data
- Noise-invariant document summarization techniques
- Issues in keyword search in presence of noise in unstructured text data
- Machine Translation for noisy text
- Analyzing very short communications like those on Twitter
- Techniques for analysis and mining of call-logs, transcribed calls, web
logs,chat logs, emails, tweets
- Business Intelligence (BI) applications dealing with noisy text data
- Surveys relating to noisy text analytics

For submission guidelines, please see our website:

Organizing Committee:

Lipika Dey, Innovation Labs, Tata Consultancy Services
Daniel Lopresti, Lehigh University, USA
Christoph Ringlstetter, University of Munich, Germany
Shourya Roy, Xerox India Innovation Hub, India

Program Committee:

Gady Agam, IIT, Chicago
Sophia Ananiandou, University of Manchester, UK
Indrajit Bhattacharya, IISc India
David Doermann, University of Maryland CP
Tanveer A. Faruquie, IBM Research, India
Gernot A. Fink, TU Dortmund, Germany
Jenifer Foster, Dublin City University, Ireland
Basilis Gatos, IIT, Demokritos
Randy Goebel, University of Alberta, Canada
Gareth Jones, Dublin City University, Ireland
Marcus Liwicki, DFKI, Germany
Volker Märgner, University of Braunschweig
Vincent Ng, Univ. of Texas at Dallas, USA
Roberto Basili, University of Roma
B. Ravindran, IIT Madras
Sebastoam Pena Saldarriaga, Synchromedia ETS
Eric Ringger, Bringham Young University
Klaus U. Schulz, University of Munich, Germany
Frederique Segond, XEROX Research Center Europe
Maosong Sun, Tsinghua University, China
L. Venkata Subramaniam, IBM Research, India
Hironori Takeuchi, IBM Research

Read more issues|LINGUIST home page|Top of issue

Page Updated: 02-Jun-2011

Supported in part by the National Science Foundation       About LINGUIST    |   Contact Us       ILIT Logo
While the LINGUIST List makes every effort to ensure the linguistic relevance of sites listed on its pages, it cannot vouch for their contents.