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Introduction to Ontology

Introduction to Ontology. In 1991, ARPA Knowledge Sharing Effort revolutionized the way in which intelligent systems were built. Instead of building knowledge-based systems from scratch, it could be done by assembling reusable components.

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Introduction to Ontology

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  1. Introduction to Ontology • In 1991, ARPA Knowledge Sharing Effort revolutionized the way in which intelligent systems were built. • Instead of building knowledge-based systems from scratch, it could be done by assembling reusable components. • Since then, considerable progress has been made in developing the conceptual bases for building technology that allows knowledge-component reuse and sharing.

  2. What is an ontology? Theoretical Foundations • The word “ontology” has been taken from Philosophy, where it means a systematic explanation of existence. • An ontology defines the basic terms and relations comprising the vocabulary of a topic area as well as the rules for combining terms and relations to define extensions to the vocabulary. • An ontology includes not only terms that are explicitly defined but also the terms that can be inferred using rules.

  3. Gruber’s (1993) definition of ontology becomes widely used: “an ontology is an explicit specification of a conceptualization”.

  4. What principles should I follow to build ontologies? • Clarity and Objectivity • Completeness • Coherence • Maximize monotonic extendibility: It means that new general or specialized terms should be included in the ontology in such a way as does not require the revision of existing definitions • Minimal ontological commitments

  5. Ontological Distinction Principle: the classes in an ontology should be disjoint • Diversification of hierarchies • Modularity: to minimize coupling between modules • Minimize the semantic distance between sibling concepts • Standardize names whenever possible

  6. What are the components of ontologies? Knowledge in ontologies are formalized using five kinds of components: classes, relations, functions, axioms and instances.

  7. What types of ontologies already exist? There are already several categories of ontologies: • Knowledge Representation Ontologies: capture the representation primitives used to formalize knowledge. • General/Common Ontologies: include vocabulary related to things, events, time, space, causality, behavior, function • Meta-ontologies (also called Generic Ontologies or Core Ontologies): reusable across domains. • Domain ontologies: reusable in a given domain. They provide vocabularies about the concepts within a domain + theories and elementary principles governing that domain. • Task ontologies: provide a systematized vocabulary of the terms used to solve problems associated with tasks. • Domain-Task ontologies • Application ontologies: contain necessary knowledge for modeling a particular domain

  8. Most well-known ontologies • Knowledge Representation Ontology: Frame Ontology by Gruber (1993) • Common Sense Ontology: Cyc Ontology (Lenat et al.,1990) provides a vast amount of fundamental human knowledge. • Linguistic Ontologies: Generalized Upper Model (GUM) (Bateman et al.,1995) and Wordnet (Miller, 1990) and Sensus (Swartout et al., 1997)

  9. Language and Environments for Building Ontologies • Ontolingua is a language based on KIF (Knowledge Interchange Format): representing declarative knowledge • LOOM is a high-level programming language based on first-order logic and environment, which belongs to KL-ONE family. • FLogic is an integration of frame-based language and first-order predicate calculus. • Protégé by Stanford University

  10. Applications that use ontologies • Although ontologies can be used to communicate between systems, people, and organizations, interoperate between systems, and support the design and development of knowledge-based and general software systems, the number of applications built that use ontologies to model the application knowledge is small.

  11. Applications that use ontologies (cont.) There exist several applications that use natural language ontologies • GUM is used in Penman text generator, TechDoc, which provides multilingual generation of technical texts, and AlFresco, an information retrieval system in the domain of Italian art history, for example. There are also applications in Enterprises domain such as the Integrated Supply Chain Management Project, a network of cooperating intelligent agents perform one or more supply chain functions. Ontology-based WWW brokers such as Ontobroker, providing brokering service for knowledge management.

  12. Reference A. Gómez-Pérez, Ontological Engineering: A State of the Art [Online], Available From: www.comp.rgu.ac.uk/staff/nw/ExpertUpdate/ontologies.ps

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