LINGUIST List 12.1075

Tue Apr 17 2001

Confs: Empirical Methods in Natural Lang Processing

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  1. Priscilla Rasmussen, Empirical Methods in Natural Language Processing (EMNLP 2001)

Message 1: Empirical Methods in Natural Language Processing (EMNLP 2001)

Date: Mon, 16 Apr 2001 16:23:14 EDT
From: Priscilla Rasmussen <rasmussecs.rutgers.edu>
Subject: Empirical Methods in Natural Language Processing (EMNLP 2001)

 *** PRELIMINARY CALL FOR PARTICIPATION IN EMNLP 2001 ***

2001 Conference on Empirical Methods in Natural Language Processing

Sponsored by SIGDAT and the Intelligent Information Systems Institute (IISI)

- -------------------------------------------------------

SIGDAT, the Association for Computational Linguistics' special
interest group on linguistic data and corpus-based approaches to NLP,
invites participation at EMNLP 2001 at Carnegie Mellon University,
Pittsburgh, PA USA on June 3 and 4, immediately preceding the meeting
of the North American Chapter of the ACL (NAACL 2001). 

We anticipate an exciting program devoted to advances in all areas of
traditional interest to the SIGDAT and related fields, as well as to
this year's theme:
 "What Works and What Doesn't: Successes and Challenges".
We'll have two days of paper presentations, panels, and invited talks,
including an invited talk by Eric Brill of Microsoft Research.

URL: http://www.cs.cornell.edu/home/llee/emnlp.html

Registration: see http://www.cs.cmu.edu/~ref/naacl/registration-forms.html
 * Early registration: by April 30 
 * Late registration: May 1-26 
 * On site registration also available

Talks/Panels: to be announced. Confirmed: Eric Brill, Microsoft Research.

Papers accepted for presentation:
- ------------------------------
Information Extraction using the Structured Language Model
Ciprian Chelba and Milind Mahajan

Knowledge Sources for Word-Level Translation Models
Philipp Koehn and Kevin Knight

Limitations of Co-training for Natural Language Learning from Large Datasets
David Pierce and Claire Cardie

Question Answering Using a Large Text Database: A Machine Learning Approach
Hwee Tou Ng, Jennifer Lai Pheng Kwan, and Yiyuan Xia

Stacking classifiers for anti-spam filtering of e-mail
Georgios Sakkis, Ion Androutsopoulos, Georgios Paliouras, Vangelis
Karkaletsis, Constantine D. Spyropoulos, and Panagiotis Stamatopoulos

A Sequential Model for Multi-class Classification
Yair Even-Zohar and Dan Roth

Creating Concise and Coherent Extract Summaries of Multi-Party Conversations
in Unrestricted Domains
Klaus Zechner

Feature Space Restructuring for SVMs with Application to Text Categorization
Hiroya Takamura and Yuji Matsumoto

Comparing Data-driven Learning Algorithms for PoS Tagging of Swedish
Beata Megyesi

Classifying Semantic Relations between Noun Compounds using a
Domain-Specific Lexical Hierarchy
Barbara Rosario and Marti Hearst

Automatic Corpus-based Tone Prediction using K-ToBI Representation
Jin-seok Lee, Byeongchang Kim and Gary Geunbae Lee

Event Segmentation of Consumer Photographs using Information Extraction from
Spoken Annotations
Amanda Stent and Alexander Loui

Using Bins to Empirically Estimate Term Weights for Text Categorization
Carl Sable and Ken Church

Using Shallow NLP in Adaptive Information Extraction from Web-related Texts
Fabio Ciravegna

Detecting short passages of similar text in large document collections
Caroline Lyon, Bob Dickerson and James Malcolm

Impact of quality and quantity of corpora on stochastic generation
Srinivas Bangalore, John Chen, and Owen Rambow

Improving Lexical Mapping Model of English-Korean Bitext Using Structural
Features
Seonho Kim, Juntae Yoon and Mansuk Song

Corpus Variation and Parser Performance
Daniel Gildea

The Unknown Word Problem: A Morphological Analysis of Japanese Using Maximum
Entropy Aided by a Dictionary
Kiyotaka Uchimoto, Satoshi Sekine, Hitoshi Isahara

Latent Semantic Analysis for Text Segmentation
Freddy Y. Y. Choi, Peter Wiemer-Hastings, and Johanna Moore

Hybrid text mining for finding abbreviations and their definitions
Youngja Park and Roy J. Byrd

Is Knowledge-Free Induction of Multiword Unit Dictionary Headwords a Solved
Problem?
Patrick Schone and Daniel Jurafsky

Learning Within-Sentence Semantic Coherence
Elena Eneva, Rose Hoberman, and Lucian Lita

Probabilistic Context-Free Grammars for Syllabification and
Grapheme-to-Phoneme Conversion
Karin Mueller

Program Committee
- ---------------

Program Chair: Lillian Lee, Cornell University (lleecs.cornell.edu)
Program Co-Chair: Donna Harman, NIST (donna.harmannist.gov)
Publication Chair: David Yarowsky, Johns Hopkins University
(yarowskycs.jhu.edu)

Regina Barzilay, Columbia University 
Thorsten Brants, Xerox 
Chris Brew, Ohio State University 
Eugene Charniak, Brown University 
Key-Sun Choi, KAIST 
Ken Church, AT&T Research 
Stephen Clark, University of Edinburgh 
Michael Collins, AT&T Research 
Eric Gaussier, Xerox 
Marti Hearst, UC Berkeley 
Don Hindle, AnswerLogic 
Changning Huang, Microsoft 
Rebecca Hwa, University of Maryland 
Hitoshi Iida, Sony 
Paul Jacobs, AnswerLogic 
Christian Jacquemin, LIMSI 
Maghi King, University of Geneva 
Wessel Kraaij, TNO-TPD 
Maria Lapata, Saarland University/University of Edinburgh 
Elizabeth Liddy, Syracuse University 
Marc Light, MITRE 
Dekang Lin, University of Alberta 
Kim-Teng Lua, National University of Singapore 
Llums M`rquez, Technical University of Catalonia 
Diana McCarthy, University of Sussex 
Helen Meng, The Chinese University of Hong Kong 
Paola Merlo,University of Geneva 
Rada Mihalcea, Southern Methodist University 
Guenter Neumann, DFKI 
Jian-Yun Nie, University of Montreal 
Franz Josef Och, RWTH Aachen 
Ted Pedersen, University of Minnesota,Duluth 
Roni Rosenfeld, Carnegie Mellon University 
Erik Tjong Kim Sang, University of Antwerp 
Anoop Sarkar, University of Pennsylvania 
Paola Velardi, University of Rome "La Sapienza" 
Atro Voutilainen, Conexor 
Kiri Wagstaff, Cornell University 
Roman Yangarber, New York University 
Joe Zhou, Intel 
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