| Автор | LEE, SEUNGMI |
| Автор | CHOI, KEY-SUN |
| Дата выпуска | 1999 |
| dc.description | A probabilistic parameter reestimation algorithm plays a key role in the automatic acquisition of stochastic grammars. In the case of context-free phrase structure grammars, the inside-outside algorithm is widely used. However, it is not directly applicable to Probabilistic Dependency Grammar (PDG), because PDG is not based on constituents but on a head-dependent relation between pairs of words. This paper presents a reestimation algorithm which is a variation of the inside-outside algorithm adapted to probabilistic dependency grammar. The algorithm can be used either to reestimate the probabilistic parameters of an existing dependency grammar, or to extract a PDG from scratch. Using the algorithm, we have learned a PDG from a part-of-speech-tagged corpus of Korean, which showed about 62·82% dependency accuracy (the percentage of correct dependencies) for unseen test sentences. |
| Издатель | Cambridge University Press |
| Название | A reestimation algorithm for probabilistic dependency grammars |
| Electronic ISSN | 1469-8110 |
| Print ISSN | 1351-3249 |
| Журнал | Natural Language Engineering |
| Том | 5 |
| Первая страница | 251 |
| Последняя страница | 270 |
| Аффилиация | LEE SEUNGMI; Center for Artificial Intelligence Research, Korea Advanced Institute of Science and Technology |
| Аффилиация | CHOI KEY-SUN; Center for Artificial Intelligence Research, Korea Advanced Institute of Science and Technology |
| Выпуск | 3 |
