Model Driven Architecture and Ontology Development - download pdf or read online

By Dragan Gaševic, Dragan Djuric, Vladan Devedžic, Bran V. Selic

ISBN-10: 3540321802

ISBN-13: 9783540321804

ISBN-10: 3540321829

ISBN-13: 9783540321828

Defining a proper area ontology is usually thought of an invaluable, to not say priceless step in virtually each software program undertaking. the reason is, software program bargains with rules instead of with self-evident actual artefacts. despite the fact that, this improvement step is infrequently performed, as ontologies depend upon well-defined and semantically strong AI strategies comparable to description logics or rule-based platforms, and such a lot software program engineers are mostly unexpected with those. Ga?evic and his co-authors attempt to fill this hole via overlaying the topic of MDA software for ontology improvement at the Semantic net. half I in their publication describes latest applied sciences, instruments, and criteria like XML, RDF, OWL, MDA, and UML. half II provides the 1st specified description of OMG’s new ODM (Ontology Definition Metamodel) initiative, a specification that is anticipated to be within the type of an OMG language like UML. eventually, half III is devoted to functions and sensible points of constructing ontologies utilizing MDA-based languages. The e-book is supported by way of an internet site displaying many ontologies, UML and different MDA-based versions, and the variations among them. "The ebook is both suited for those that basically are looking to learn of the proper technological panorama, to practitioners facing concrete difficulties, and to researchers looking tips to probably fruitful parts of analysis. The writing is technical but transparent and obtainable, illustrated all through with valuable and simply digestible examples." from the Foreword through Bran Selic, IBM Rational software program, Canada. "I have no idea one other e-book that gives the sort of prime quality perception into UML and ontologies." Steffen Staab, U Koblenz, Germany

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Model Driven Architecture and Ontology Development by Dragan Gaševic, Dragan Djuric, Vladan Devedžic, Bran V. PDF

Defining a proper area ontology is usually thought of an invaluable, to not say important step in virtually each software program undertaking. it is because software program offers with rules instead of with self-evident actual artefacts. even if, this improvement step is rarely performed, as ontologies depend upon well-defined and semantically robust AI recommendations corresponding to description logics or rule-based structures, and such a lot software program engineers are principally surprising with those.

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Invoke a procedure). Another interpretation of rules, premises, and conclusions is obtained from the state–transition view. There is a collection of states – situations that might occur in the application environment. A rule describes the logic of moving from a start state (a set of valid premises) to a goal state (described by the rule’s conclusions). Uncertain rules may include certainty factors, both in the premises and in the conclusions, and imply uncertain inferences. 5) In uncertain rules, omitting an explicit value for a certainty factor in a premise means “take the previously inferred CF value” or “take the default CF value”.

Alternatively, the environment may provide an application program interface (API) with appropriate functions through which programs can operate on the knowledge base in terms of adding, retracting, and modifying concepts, roles, and assertions. 2 Frame-Based Representation Languages In all frame-based representation languages (or, for simplicity, “frame representation languages”), the central tenet is a notation based on the specification of frames (concepts and classes), their instances (objects and individuals), their properties, and their relationships to each other [Welty, 1996].

22 1. Knowledge Representation Propositional Logic A proposition is a logical statement that is either true or false. ” An O–A–V triplet is a more complex form of proposition, since it has three distinct parts. Propositional logic is a form of symbolic reasoning. It assigns a symbolic variable to a proposition, for example A = The princess is in the palace The truth value (true or false) of the variable represents the truth of the corresponding statement (the proposition). Propositions can be linked by logical operators (AND (), OR (), NOT (), IMPLIES (o or ), and EQUIVALENCE ()) to form more complex statements and rules: IF AND THEN The princess is in the palace The king is in the garden The king cannot see the princess (A) (B) (C) The symbolic representation of the above rule in propositional logic is AB o C Thus, propositional logic allows formal and symbolic reasoning with rules, by deriving truth values of propositions using logical operators and variables.

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