By Andrea Calì, Georg Gottlob, Andreas Pieris (auth.), Pascal Hitzler, Thomas Lukasiewicz (eds.)

This e-book constitutes the refereed lawsuits of the 4th overseas convention on internet Reasoning and Rule platforms, RR 2010, held in Brixen-Bressanone, Italy, in September 2010. The nine revised complete papers, 6 revised brief papers, and four poster papers provided including 1 PhD paper, 2 method descriptions and three invited papers have been rigorously reviewed and chosen from forty-one submissions. The papers tackle all present issues in internet reasoning, Web-based wisdom, and rule platforms similar to illustration options; ideas and ontologies; reasoning languages; potency and benchmarking,; ontology languages; querying and optimization; reasoning with uncertainty, below inconsistency, and with constraints; rule languages and structures; rule interchange codecs and markup languages; scalability; approximate reasoning; statistical tools and symbolic reasoning; in addition to semantic internet providers modeling and functions.

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In Fig. 4, the graduate courses in question may or may not involve the use of (up to 2) department labs. “Among which” inner boxes contain clusters representing individuals that belong to subclasses of one or more classes specified in the outer box. In Fig. 4, the attendance of the graduate courses in question consists of students, some of which are required to be graduate students. Optionally, guests may attend. The above remarks are included here only for pedagogical purposes. In fact, we define the precise semantics of model outlines by means of algorithm Descr, which, when given a model outline C (in abstract syntax), yields the ALCN concept description taken as the meaning of C.

Dashed clusters for Cn+1 , . . , Cp are created in the main target box for the R-arrow. In our example description, in lines (2h)–(2j), we have that n = 1, and C1 = Student, and D = Enrolled, and p = 1, and C2 = Guest, and q = 1, and F1 = GradStudent. 5 Evaluation We have conducted a usability study in order to evaluate our proposed diagrammatic notation. The main aim was to test the usefulness of model outlines for the understanding of complex concept descriptions. Note that it is the model outline notation itself that is being evaluated, not a specific graphical user interface (GUI) implementing the notation.

To account for labeled optional clusters) and give a more informal explanation of the main steps involved in such a translation, using as a working example the concept description that originated the model outline in Fig. 4. Given an ALCN concept description C, we start by converting C to modified disjunctive normal form (mDNF), applying simplification rules in the process. A concept description is in mDNF if it fits the pattern D1 ... C , where C is itself in mDNF. R). R). Usability of a Visual Language for DL Concept Descriptions Descr(C) 1 2 3 4 5 6 7 8 9 ✄ C has the form ( cases C1 · · · Cm ) Descr ← ⊥ ✄ Ci has the form ( cluster S L ( A1 · · · An ) ) for each Ci in C1 , .

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