Paper: Handling Sparse Data By Successive Abstraction

ACL ID C96-2151
Title Handling Sparse Data By Successive Abstraction
Venue International Conference on Computational Linguistics
Session Main Conference
Year 1996
Authors

on Christer Samuelsson Universit£t des Saarlandes, FR 8.7, Computcrlinguistik Postfach 1150, D-66041 Saarbrfickcn, Germany Internet: christer©coli.uni-sb, de Abstract A general, practical method for hand- ling sparse data that avoids held-out data and iterative reestimation is derived from first principles. It has been tested on a part-of-speech tagging task and out- performed (deleted) interpolation with context-independent weights, even when the latter used a globally optimal para- meter setting determined a posteriori.