| Texto completo | |
| Autor(es): |
Ochoa-Luna, Jose Eduardo
;
Revoredo, Kate
;
Cozman, Fabio Gagliardi
;
Batyrshin, I
;
Sidorov, G
Número total de Autores: 5
|
| Tipo de documento: | Artigo Científico |
| Fonte: | Lecture Notes in Computer Science; v. 7094, p. 3-pg., 2011-01-01. |
| Resumo | |
Description logics have become a prominent paradigm in knowledge representation (particularly for the Semantic Web), but they typically do not include explicit representation of uncertainty. In this paper, we propose a framework for automatically learning a Probabilistic Description Logic from data. We argue that one must learn both concept definitions and probabilistic assignments. We also propose algorithms that do so and evaluate these algorithms on real data. (AU) | |
| Processo FAPESP: | 08/03995-5 - LOGPROB: lógica probabilística - fundamentos e aplicações computacionais |
| Beneficiário: | Marcelo Finger |
| Modalidade de apoio: | Auxílio à Pesquisa - Temático |