Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4952131 | Theoretical Computer Science | 2017 | 16 Pages |
Abstract
In this survey, we will discuss current uses of finite-state information in several statistical natural language processing tasks. To this end, we will review standard approaches in tokenization, part-of-speech tagging, and parsing, and illustrate the utility of finite-state information and technology in these areas. The particular problems were chosen to allow a natural progression from simple prediction to structured prediction. We aim for a sufficiently formal presentation suitable for readers with a background in automata theory that allows to appreciate the contribution of finite-state approaches, but we will not discuss practical issues outside the core ideas. We provide instructive examples and pointers into the relevant literature for all constructions. We close with an outlook on finite-state technology in statistical machine translation.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Andreas Maletti,