Conference on Empirical Methods in Natural Language Processing (1999)
1999 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora
What’s Happened Since the First SIGDAT Meeting?
Kenneth Ward Church
Text-Translation Alignment: Three Languages Are Better Than Two
Michel Simard
Mapping Multilingual Hierarchies Using Relaxation Labeling
J. Daudé
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L. Padró
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G. Rigau
Improved Alignment Models for Statistical Machine Translation
Franz Josef Och
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Christoph Tillmann
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Hermann Ney
Cross-Language Information Retrieval for Technical Documents
Atsushi Fujii
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Tetsuya Ishikawa
Boosting Applied to Tagging and PP Attachment
Steven Abney
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Robert E. Schapire
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Yoram Singer
Applying Extrasentential Context To Maximum Entropy Based Tagging With A Large Semantic And Syntactic Tagset
Ezra Black
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Andrew Finch
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Ruiqiang Zhang
Improving POS Tagging Using Machine-Learning Techniques
Lluis Marquez
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Horacio Rodriguez
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Josep Carmona
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Josep Montolio
Determining the specificity of nouns from text
Sharon A. Caraballo
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Eugene Charniak
Retrieving Collocations From Korean Text
Seonho Kim
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Zooil Yang
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Mansuk Song
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Jung-Ho Ahn
Noun Phrase Coreference as Clustering
Claire Cardie
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Kiri Wagstaff
Language Independent Named Entity Recognition Combining Morphological and Contextual Evidence
Silviu Cucerzan
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David Yarowsky
Unsupervised Models for Named Entity Classification
Michael Collins
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Yoram Singer
Hybrid Disambiguation of Prepositional Phrase Attachment and Interpretation
Sven Hartrumpf
HMM Specialization with Selective Lexicalization
Jin-Dong Kim
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Sang-Zoo Lee
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Hae-Chang Rim
Why Doesn’t Natural Language Come Naturally?
Richard Schwartz
POS Tags and Decision Trees for Language Modeling
Peter A. Heeman
An Information-Theoretic Empirical Analysis of Dependency-Based Feature Types for Word Prediction Models
Dekai Wu
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Jun Zhao
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Zhifang Sui
Word Informativeness and Automatic Pitch Accent Modeling
Shimei Pan
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Kathleen R. McKeown
Learning Discourse Relations with Active Data Selection
Tadashi Nomoto
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Yuji Matsumoto
A Learning Approach to Shallow Parsing
Marcia Muñoz
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Vasin Punyakanok
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Dan Roth
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Dav Zimak
Guiding a Well-Founded Parser with Corpus Statistics
Amon Seagull
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Lenhart Schubert
Exploiting Diversity in Natural Language Processing: Combining Parsers
John C. Henderson
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Eric Brill
Lexical ambiguity and Information Retrieval revisited
Julio Gonzalo
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Anselmo Penas
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Felisa Verdejo
Detecting Text Similarity over Short Passages: Exploring Linguistic Feature Combinations via Machine Learning
Vasileios Hatzivassiloglou
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Judith L. Klavans
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Eleazar Eskin
Automatic Construction of Weighted String Similarity Measures
Jorg Tiedemann
Taking the load off the conference chairs-towards a digital paper-routing assistant
David Yarowsky
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Radu Florian
PP-Attachment: A Committee Machine Approach
Martha A. Alegre
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Josep M. Sopena
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Agusti Lloberas
Cascaded Grammatical Relation Assignment
Sabine Buchholz
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Jorn Veenstra
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Walter Daelemans
Automatically Merging Lexicons that have Incompatible Part-of-Speech Categories
Daniel Ka-Leung Chan
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Dekai Wu
An Iterative Approach to Estimating Frequencies over a Semantic Hierarchy
Stephen Clark
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David Weir
Using Subcategorization to Resolve Verb Class Ambiguity
Maria Lapata
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Chris Brew
Improving Brill’s POS Tagger for an Agglutinative Language
Beata Megyesi
Corpus-Based Learning for Noun Phrase Coreference Resolution
Wee Meng Soon
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Hwee Tou Ng
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Chung Yong Lim
Corpus-Based Approach for Nominal Compound Analysis for Korean Based on Linguistic and Statistical Information
Juntae Yoon
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Key-Sun Choi
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Mansuk Song