Papers for Relevance Assessment by Art Munson

Research Question: How well does greedy ensemble selection optimize difficult and cumbersome performance metrics for natural language processing problems?

Paper ID
(Link to PDF)

Title

Author(s)

W05-0628

Semantic Role Labeling as Sequential Tagging

Lluis Ma rquez; Pere Comas; Jesus Gimenez; Neus Catala 

83_Paper

Ensemble-based Active Learning for Parse Selection

Miles Osborne and Jason Baldridge

W02-1008

Combining Sample Selection and Error-Driven Pruning for Machine Learning of Coreference Rules

Vincent Ng; Claire Cardie

A00-2009

A Simple Approach to Building Ensembles of Naive Bayesian Classifiers for Word Sense Disambiguation

Ted Pedersen

4-zelenko

Coreference Resolution for Information Extraction

Dmitry Zelenko, Chinatsu Aone and Jason Tibbetts

W02-1029

Ensemble Methods for Automatic Thesaurus Extraction

James Curran

W03-0403

Active learning for HPSG parse selection

Jason Baldridge; Miles Osborne

N03-1023

Weakly Supervised Natural Language Learning Without Redundant Views

Vincent Ng; Claire Cardie

328_pdf_2-col

Learning Noun Phrase Anaphoricity to Improve Conference Resolution: Issues in Representation and Optimization

Vincent Ng

W99-0611

Noun Phrase Coreference as Clustering

Claire Cardie; Kiri Wagstaf

W02-1004

Modeling Consensus: Classifier Combination for Word Sense Disambiguation

Radu Florian; David Yarowsky

I05-2033

POS Tagger Combinations on Hungarian Text

Andras Kuba; Laszlo Felfoldi; Andras Kocsor

C02-1139

Identifying Anaphoric and Non-Anaphoric Noun Phrases to Improve Coreference Resolution

Vincent Ng; Claire Cardie

W99-0608

Improving POS Tagging Using Machine-Learning Techniques

Lluis Marquez; Horacio Rodriguez; Josep Carmona; Josep Montolio

W01-1614

Empirical Methods for Evaluating Dialog Systems

Tim Paek