Program - Feature Engineering for Machine Learning in Natural Language Processing

Feature Engineering for Machine Learning in Natural Language Processing

WORKSHOP PROGRAM

Wednesday, June 29, 2005
8:45–9:00	Opening Remarks
	Session W4.1: Classification
	A Novel Machine Learning Approach for the Identification of Named Entity Relations Tianfang Yao and Hans Uszkoreit
	Feature Engineering and Post-Processing for Temporal Expression Recognition Using Conditional Random Fields Sisay Fissaha Adafre and Maarten de Rijke
	Temporal Feature Modification for Retrospective Categorization Robert Liebscher and Richard K. Belew
10:30–11:00	Break
11:00–12:00	Invited Talk by Andrew McCallum
	Using Semantic and Syntactic Graphs for Call Classification Dilek Hakkani-Tür, Gokhan Tur and Ananlada Chotimongkol
12:30–14:00	Lunch
	Session W4.2: Discourse and Syntax
	Feature-Based Segmentation of Narrative Documents David Kauchak and Francine Chen
	Identifying Non-Referential it: A Machine Learning Approach Incorporating Linguistically Motivated Patterns Adriane Boyd, Whitney Gegg-Harrison and Donna Byron
	Engineering of Syntactic Features for Shallow Semantic Parsing Alessandro Moschitti, Bonaventura Coppola, Daniele Pighin and Roberto Basili
15:30–16:00	Break
	Session W4.3: Feature Sources
	Automatic Identification of Sentiment Vocabulary: Exploiting Low Association with Known Sentiment Terms Michael Gamon and Anthony Aue
	Studying Feature Generation from Various Data Representations for Answer Extraction Dan Shen, Geert-Jan M. Kruijff and Dietrich Klakow