objects are taken into account, the basic deductive task for retrieving information from a knowledge base is instance checking, that amounts to checking whether the knowledge base implies that an individual is an instance of a given concept. In this paper, we address the question of whether instance

objects are taken into account, the basic deductive task for retrieving information from a knowledge base is instance checking, that amounts to checking whether the knowledge base implies that an individual is an instance of a given concept. In this paper, we address the question of whether instance

Abstract. We consider the problem of answering queries against an EL knowledge base (KB) using secrets, whenever it is possible to do so without compromising secrets. We provide a polynomial time algorithm that, given an EL KB Σ, asetS of secrets to be protected and a query q, outputs “Yes ” whenever Σ � q and the answer to q, together with the answers to any previous queries answered by the KB, does not allow the querying agent to deduce any of the secrets in S. This approach allows more flexible information sharing than is possible with traditional access control mechanisms. 1

Efficiently querying Description Logic (DL) ontologies is becoming a vital task in various data-intensive DL applications. Considered as a basic service for answering object queries over DL ontologies, instance checking can be realized by using the most specific concept (MSC) method, which converts

to reason about quantifiers. Instead of conventional matching in a term DAG, Simplify matches up to equivalence in an E-graph, which detects many relevant pattern instances that would be missed by the conventional approach. The paper describes two techniques, labels and counterexample contexts, for helping

Matching elements of two data schemas or two data instances plays a key role in data warehousing, e-business, or even biochemical applications. In this paper we present a matching algorithm based on a fixpoint computation that is usable across different scenarios. The algorithm takes two graphs

We propose a new family of Description Logics (DLs), called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts, and checking satisfiability of the whole knowledge base

A program correctness checker is an algorithm for checking the output of a computation. That is, given a program and an instance on which the program is run, the checker certifies whether the output of the program on that instance is correct. This paper defines the concept of a program checker

Abstract Recently, researchers have demonstrated that "loopy belief propagation" -the use of Pearl's polytree algorithm in a Bayesian network with loops -can perform well in the context of error-correcting codes. The most dramatic instance of this is the near Shannon

; modal, epistemic, and temporal operators; probabilities and fuzzy logic; and defaults. On the other hand, it considers non-standard inference problems for Description Logics, i.e., inference problems that-unlike subsumption or instance checking-are not available in all systems, but have turned out