EMNLP 2001 Accepted Papers

The program will also include invited talks and panels, including an invited talk by Eric Brill.

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

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

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

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