Applying Machine Learning to Discourse Processing 
AAAI 1998 Spring Symposium Series, Stanford University 
March 23-25  

Table of Contents

Long Papers

Estimating the Effectiveness of Conversational Behaviors in a Reading 
Tutor that Listens
  Gregory Aist and Jack Mostow 

Relational Learning of Pattern-Match Rules for Information Extraction
  Mary Elaine Califf and Raymond J. Mooney 

A Statistical Model for Discourse Act Recognition in Dialogue Interactions
  Jennifer Chu-Carroll 

Analyzing and Predicting Patterns of DAMSL Utterance Tags
  Mark G. Core 

Clarity: Inferring Discourse Structure from Speech
  Michael Finke, Maria Lapata, Alon Lavie, Lori Levin, Laura 
  Mayfield-Tomokiyo, Thomas Polzin, Klaus Ries, Alex Waibel, and Klaus 
  Zechner  

An Application of Explanation-Based Learning to Discourse Generation and 
Interpretation
  Nancy Green and Jill Fain Lehman 
 
Improving Ellipsis Resolution with Transformation-Based Learning
  Daniel Hardt

Identifying Discourse Markers in Spoken Dialog
  Peter A. Heeman, Donna Byron and James F. Allen 

Using Machine Learning to Identify Intonational Segments
  Julia Hirschberg and Christine H. Nakatani

Learning Embedded Discourse Mechanisms for Information Extraction
  Andrew Kehler 
  
Learning Constraints for Plan-Based Discourse Processors with Genetic 
Programming
  Marc Mason and Carolyn Penstein Rose 

Using Unsupervised Learning for Engineering of Spoken Dialogues
  Jens-Uwe Moeller

Lexical Clustering and Definite Description Interpretation
  Massimo Poesio, Sabine Schulte im Walde, and Chris Brew 

Computing Dialogue Acts from Features with Transformation-Based Learning
  Ken Samuel, Sandra Carberry, and K. Vijay-Shanker 

Dialog Act Modeling for Conversational Speech
  Andreas Stolcke, Elizabeth Shriberg, Rebecca Bates, Noah Coccaro, Daniel 
  Jurafsky, Rachel Martin, Marie Meteer, Klaus Ries, Paul Taylor, and Carol 
  Van Ess-Dykema

Collocation Properties in Probabilistic Classifiers for Discourse 
Categorization
  Janyce M. Wiebe and Kenneth McKeever 

Short Papers

SGML-Based Markup as a Step toward Improving Knowledge Acquisition for Text 
Generation
  Reva Freedman, Yujian Zhou, Jung Hee Kim, Michael Glass, and Martha Evens 

Automating Coreference: The Role of Annotated Training Data
  Lynette Hirschman, Patricia Robinson, John Burger, and Marc Vilain

Towards Automated Analysis of Spoken Discourse Using Discourse Topology
  Susann Luperfoy and David Duff 

Improving Dialogue Annotation Reliability
  Teresa Sikorski