Axiom pinpointing has been introduced in description logics (DLs) to help the user understand the reasons why consequences hold by computing minimal subsets of the knowledge base that have the consequence in question. Until now, the pinpointing approach has only been applied to the DL ALC and some of its extensions. This paper considers axiom pinpointing in the less expressive DL EL + , for which subsumption can be decided in polynomial time. More precisely, we consider an extension of the pinpointing problem where the knowledge base is divided into a static part, which is always present, and a refutable part, of which subsets are taken. We describe an extension of the subsumption algorithm for EL + that can be used to compute all minimal subsets of (the refutable part of) a given TBox that imply a certain subsumption relationship. The worst-case complexity of this algorithm turns out to be exponential. This is not surprising since we can show that a given TBox may have exponentially many such minimal subsets. However, we can also show that the problem is not even output polynomial, i.e., unless P=NP, there cannot be an algorithm computing all such minimal sets that is polynomial in the size of its input and output. In addition, we show that finding out whether there is such a minimal subset within a given cardinality bound is an NP-complete problem. In contrast to these negative results, we also show that one such minimal subset can be computed in polynomial time. Finally, we provide some encouraging experimental results regarding the performance of a practical algorithm that computes one (small, but not necessarily minimal) subset that has a given subsumption relation as consequence.

No abstract

No abstract

No abstract

Description Logics (DLs) are a family of logicbased knowledge representation formalisms, which can be used to develop ontologies in a formally well-founded way. The standard reasoning service of subsumption has proved indispensable in ontology design and maintenance. This checks, relative to the logical definitions in the ontology, whether one concept is more general/specific than another. When no subsumption relationship is identified, however, no information about the two concepts can be given. This work presents a new notion of semantic similarity which stems from the known homomorphism-based structural subsumption algorithm. The proposed similarity measure computes a numerical degree of similarity between two ℰℒ concept descriptions despite not being in the subsumption relation.

No abstract

This paper describes a collaborative approach to ontology development for data qualification for life cycle assessment by taking into consideration the Life Cycle Inventory (LCI) and Data Quality Indicator (DQI). The developed ontology is integrated with rule-based knowledge, to provide userdefined policies for LCI based on DQI. An ontology application management framework is developed to provide a collaborative environment for knowledge engineers and domain experts to define the knowledge explication and recommendation rules based on usage scenario. LCI data from agricultural domain is collected, and mapped to the knowledge base. To demonstrate the advantage of transformed rules, a scenario-based recommender system is built on top of the ontology, and carries out data quality measurement.

Reification of parthood relations according to the SEP-triplet encoding pattern has been employed in the clinical terminology SNOMED CT to simulate transitivity of the part-of relation via transitivity of the is-a relation and to inherit properties along part-of links. In this paper we argue that using a more expressive representation language, which allows for a direct representation of the relevant properties of the part-of relation, makes modelling less error prone while having no adverse effect on the efficiency of reasoning.