By Asuncion Gomez-Perez, Oscar Corcho, Mariano Fernandez-Lopez
Ontological Engineering refers back to the set of actions that quandary the ontology improvement strategy, the ontology lifestyles cycle, the equipment and methodologies for construction ontologies, and the instrument suites and languages that aid them. over the past decade, expanding realization has been fascinated about ontologies and Ontological Engineering. Ontologies are actually primary in wisdom Engineering, synthetic Intelligence and desktop technological know-how; in functions on the topic of wisdom administration, common language processing, e-commerce, clever integration details, info retrieval, integration of databases, b- informatics, and schooling; and in new rising fields just like the Semantic net. basic targets of this publication are to acquaint scholars, researchers and builders of data platforms with the fundamental ideas and significant problems with Ontological Engineering, in addition to to make ontologies extra comprehensible to these desktop technological know-how engineers that combine ontologies into their info structures. we now have paid particular consciousness to the effect that ontologies have at the Semantic internet. tips to the Semantic net seem in the entire chapters, yet specifically within the bankruptcy on ontology languages and instruments.
Read Online or Download Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. First Edition (Advanced Information and Knowledge Processing) PDF
Similar information theory books
Krippendorff introduces social scientists to details conception and explains its software for structural modeling. He discusses key subject matters similar to: find out how to make certain a knowledge conception version; its use in exploratory examine; and the way it compares with different ways resembling community research, course research, chi sq. and research of variance.
The on-demand financial system is reversing the rights and protections employees fought for hundreds of years to win. usual web clients, in the meantime, preserve little keep watch over over their own facts. whereas promising to be the nice equalizers, on-line structures have frequently exacerbated social inequalities. Can the net be owned and ruled another way?
- Probability and Information Theory with Applications to Radar
- H.264 and MPEG-4 Video Compression: Video Coding for Next Generation Multimedia
- Selected Problems of Fractional Systems Theory
- Information Theory and Coding - Solved Problems
- Treatise on Analysis
- Flows in Transportation Networks
Additional info for Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. First Edition (Advanced Information and Knowledge Processing)
Z)))))))) Reasoning in DL is mostly based on the subsumption test among concepts. For instance, we can explicitly say that the following two classes are disjoint: the class TrainTravel, and the class that is a Travel, whose arrivalPlace is a EuropeanLocation and whose departurePlace is a USALocation. From the disjointness of these two classes, we can infer that travels by train between Europe and the USA are not possible. As this knowledge cannot be represented in LOOM we represent it in OIL, another DL language: 20 Ontological Engineering disjoint TrainTravel (Travel and (slot-constraint value-type and (slot-constraint value-type arrivalPlace EuropeanLocation) departurePlace USALocation)) Individuals represent instances of concepts and the values of their roles (properties).
In our example, subclasses of the concept travel could be: flight, train travel, etc. Formal is-a hierarchies that include instances of the domain. In this case, we would include instances of flights: the flight AA7462 arrives in Seattle, departs on February 8, and costs 300$. Theoretical Foundations of Ontologies x x x 29 Frames. The ontology includes classes and their properties, which can be inherited by classes of the lower levels of the formal is-a taxonomy. In our example, a travel has a unique departure date and an arrival date, a company name and at most one price for a single fare with the company.
Every SQL version permits, at least, defining views using query expressions as expressive as those written in Datalog (Ullman, 1988) except for recursive expressions. Datalog is the Prolog’s counterpart for databases, and it is used to build databases from a logic view point. According to the former paragraphs, database technology can be used to build ontologies, although such a technology is not always the most appropriate one for heavyweight ontology construction. In the linear continuum from lightweight to heavyweight ontologies, the domain model expressed in an ER diagram is the lightest one, the one expressed in SQL is heavier and the one expressed in Datalog is the heaviest one.