Paper: An Analogical Learner For Morphological Analysis

ACL ID W05-0616
Title An Analogical Learner For Morphological Analysis
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2005

Analogical learning is based on a two- step inference process: (i) computation of a structural mapping between a new and a memorized situation; (ii) transfer of knowledge from the known to the un- known situation. This approach requires the ability to search for and exploit such mappings, hence the need to properly de- fine analogical relationships, and to effi- ciently implement their computation. In this paper, we propose a unified defini- tion for the notion of (formal) analogical proportion, which applies to a wide range of algebraic structures. We show that this definition is suitable for learning in do- mains involving large databases of struc- tured data, as is especially the case in Nat- ural Language Processing (NLP). We then present experimental results obtained on two morphologi...