This paper deals with learning in AL-log, a hybrid language that merges the function-free Horn clause language DATALOG and the description logic ALC. Our application context is descriptive data mining. We introduce O-queries, a rule-based form of unary conjunctive queries in AL-log, and a generality order greater than or equal toB for structuring spaces of O-queries. We define a (downward) refinement operator po for greater than or equal to (B)-ordered spaces of O-queries, prove its ideality and discuss an efficient implementation of it in the context of interest.
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Titolo: | Ideal Refinement of Descriptions in AL-log |
Autori: | |
Data di pubblicazione: | 2003 |
Rivista: | |
Abstract: | This paper deals with learning in AL-log, a hybrid language that merges the function-free Horn clause language DATALOG and the description logic ALC. Our application context is descriptive data mining. We introduce O-queries, a rule-based form of unary conjunctive queries in AL-log, and a generality order greater than or equal toB for structuring spaces of O-queries. We define a (downward) refinement operator po for greater than or equal to (B)-ordered spaces of O-queries, prove its ideality and discuss an efficient implementation of it in the context of interest. |
Handle: | http://hdl.handle.net/11586/137205 |
ISBN: | 978-3-540-20144-1 |
Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |