SUNDAY, JUNE 3
8:45	9:00	Welcome
		Session I: Learning
9:00	9:25	Limitations of Co-Training for Natural Language Learning from Large Datasets
		David Pierce and Claire Cardie
9:25	9:50	A Sequential Model for Multi-Class Classification
		Yair Even-Zohar and Dan Roth
9:50	10:15	Learning Within-Sentence Semantic Coherence
		Elena Eneva, Rose Hoberman and Lucian Lita
10:15	10:45	Break
		Session II: Machine Translation
10:45	11:10	Knowledge Sources for Word-Level Translation Models
		Philipp Köhn and Kevin Knight
11:10	11:35	Improving Lexical Mapping Model of English-Korean Bitext Using Structural Features
		Seonho Kim, Juntae Yoon and Mansuk Song
11:35	11:45	Short break
11:45	12:45	Invited talk, Eric Brill "Paucity Shmaucity -- What Can We Do With A Trillion Words?"
12:45	2:00	LUNCH
		Session III: Text Categorization
2:00	2:25	Stacking Classifiers for Anti-Spam Filtering of E-Mail
		Georgios Sakkis, Ion Androutsopoulos, Georgios Paliouras, Vangelis Karkaletsis, Constantine D. Spyropoulos and Panagiotis Stamatopoulos
2:25	2:50	Feature Space Restructuring for SVMs with Application to Text Categorization
		Hiroya Takamura and Yuji Matsumoto
2:50	3:15	Using Bins to Empirically Estimate Term Weights for Text Categorization
		Carl Sable and Kenneth W. Church
3:15	3:25	Short break
		Session IV: Question Answering and Information Extraction
3:25	3:50	Question Answering Using a Large Text Database: A Machine Learning Approach
		Hwee Tou Ng, Jennifer Lai Pheng Kwan and Yiyuan Xia
3:50	4:15	Information Extraction Using the Structured Language Model
		Ciprian Chelba and Milind Mahajan
4:15	4:30	Short break
4:30	5:30	Panel: When does EM work? (includes an introduction to the Expectation-Maximization algorithm) Eugene Charniak, Kevin Knight, Ted Pedersen, Stefan Riezler

		MONDAY, JUNE 4
		Session V: Lexical Acquisition and Text Segmentation
8:35	9:00	Classifying the Semantic Relations in Noun Compounds via a Domain-Specific Lexical Hierarchy
		Barbara Rosario and Marti Hearst
9:00	9:25	The Unknown Word Problem: a Morphological Analysis of Japanese Using Maximum Entropy Aided by a Dictionary
		Kiyotaka Uchimoto, Satoshi Sekine and Hitoshi Isahara
9:25	9:50	Is Knowledge-Free Induction of Multiword Unit Dictionary Headwords a Solved Problem?
		Patrick Schone and Daniel Jurafsky
9:50	10:15	Latent Semantic Analysis for Text Segmentation
		Freddy Y. Y. Choi, Peter Wiemer-Hastings and Johanna Moore
10:15	10:45	Break
		Session VI: Applications
10:45	11:10	Detecting Short Passages of Similar Text in Large Document Collections
		Caroline Lyon, James Malcolm and Bob Dickerson
11:10	11:35	Hybrid Text Mining for Finding Abbreviations and their Definitions
		Youngja Park and Roy J. Byrd
11:35	11:45	Short break
11:45	12:45	Panel: What Works and What Doesn't? Industrial Perspectives Adam Berger, David Evans, Joshua Goodman, Lynette Hirschman
12:45	2:00	LUNCH
		Session VII: Spoken Language Output
2:00	2:25	Automatic Corpus-based Tone Prediction using K-ToBI Representation
		Jin-Seok Lee, Byeongchang Kim and Gary Geunbae Lee
2:25	2:50	Probabilistic Context-Free Grammars for Syllabification and Grapheme-to-Phoneme Conversion
		Karin Müller
2:50	3:00	Short break
		Session VIII: POS Tagging and Corpus Analysis
3:00	3:25	Comparing Data-Driven Learning Algorithms for PoS Tagging of Swedish
		Beáta Megyesi
3:25	3:50	Impact of Quality and Quantity of Corpora on Stochastic Generation
		Srinivas Bangalore, John Chen and Owen Rambow
3:50	4:15	Corpus Variation and Parser Performance
		Daniel Gildea
4:15	4:30	Refreshments (close)

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