Paper: Scaling up Analogical Learning

ACL ID C08-2013
Title Scaling up Analogical Learning
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2008

Recent years have witnessed a growing in- terest in analogical learning for NLP ap- plications. If the principle of analogical learning is quite simple, it does involve complex steps that seriously limit its ap- plicability, the most computationally de- manding one being the identification of analogies in the input space. In this study, we investigate different strategies for ef- ficiently solving this problem and study their scalability.