Combining Horn rules and description logics in CARIN
Artificial Intelligence
Constructing the least models for positive modal logic programs
Fundamenta Informaticae
A Hybrid System with Datalog and Concept Languages
AI*IA Proceedings of the 2nd Congress of the Italian Association for Artificial Intelligence on Trends in Artificial Intelligence
Datalog and Description Logics: Expressive Power
DBLP-6 Proceedings of the 6th International Workshop on Database Programming Languages
Description logic programs: combining logic programs with description logic
WWW '03 Proceedings of the 12th international conference on World Wide Web
Data complexity of reasoning in very expressive description logics
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Approximating horn knowledge bases in regular description logics to have PTIME data complexity
ICLP'07 Proceedings of the 23rd international conference on Logic programming
Horn Knowledge Bases in Regular Description Logics with PTIME Data Complexity
Fundamenta Informaticae
HornDL: an expressive horn description logic with PTime data complexity
RR'13 Proceedings of the 7th international conference on Web Reasoning and Rule Systems
Hi-index | 0.00 |
We study the deterministic Horn fragment of $\mathcal{ALC}$, which restricts the general Horn fragment of $\mathcal{ALC}$ only in that, the constructor ∀R.C is allowed in bodies of program clauses and queries only in the form ∀∃R.C, which is defined as ∀R.C⊓∃R.C. We present an algorithm that for a deterministic positive logic program P given as a TBox constructs a finite least pseudo-model $\mathcal{I}$ of P such that for every deterministic positive concept C, P⊧C iff $\mathcal{I}$ validates C (and more strongly, iff $\mathcal{I},\tau \models C$, where τ is the distinguished object of $\mathcal{I}$ and the satisfaction means τ is an instance of C w.r.t. $\mathcal{I}$). Pseudo-interpretations are very similar to (traditional) interpretations, except that they have two interpretation functions for roles, one to deal with the constructor ∃R.C and the other to deal with ∀R.C. They are ordered by comparing the sets of validated positive concepts. Our algorithm runs in time 2O(n) and returns a pseudo-interpretation of size 2O(n). Our method is extendable for instance checking w.r.t. knowledge bases containing also an ABox in more expressive description logics.