Paper: Text Chunking By Combining Hand-Crafted Rules And Memory-Based Learning

ACL ID P03-1063
Title Text Chunking By Combining Hand-Crafted Rules And Memory-Based Learning
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2003
Authors

This paper proposes a hybrid of hand- crafted rules and a machine learning method for chunking Korean. In the par- tially free word-order languages such as Korean and Japanese, a small number of rules dominate the performance due to their well-developed postpositions and endings. Thus, the proposed method is primarily based on the rules, and then the residual errors are corrected by adopting a memory-based machine learning method. Since the memory-based learning is an efficient method to handle exceptions in natural language processing, it is good at checking whether the estimates are excep- tional cases of the rules and revising them. An evaluation of the method yields the im- provement in F-score over the rules or var- ious machine learning methods alone.