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A translation approach to portable ontology specifications
- KNOWLEDGE ACQUISITION
, 1993
"... To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations, functions ..."
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Cited by 3365 (9 self)
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To support the sharing and reuse of formally represented knowledge among AI systems, it is useful to define the common vocabulary in which shared knowledge is represented. A specification of a representational vocabulary for a shared domain of discourse — definitions of classes, relations, functions, and other objects — is called an ontology. This paper describes a mechanism for defining ontologies that are portable over representation systems. Definitions written in a standard format for predicate calculus are translated by a system called Ontolingua into specialized representations, including frame-based systems as well as relational languages. This allows researchers to share and reuse ontologies, while retaining the computational benefits of specialized implementations. We discuss how the translation approach to portability addresses several technical problems. One problem is how to accommodate the stylistic and organizational differences among representations while preserving declarative content. Another is how to translate from a very expressive language into restricted languages, remaining system-independent while preserving the computational efficiency of implemented systems. We describe how these problems are addressed by basing Ontolingua itself on an ontology of domain-independent, representational idioms.
Agents and the Semantic Web
- IEEE INTELLIGENT SYSTEMS
, 2001
"... Many challenges of bringing communicating multiagent systems to the Web require ontologies. The integration of agent technology and ontologies could significantly affect the use of Web services and the ability to extend programs to perform tasks for users more efficiently and with less human interve ..."
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Cited by 2352 (18 self)
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Many challenges of bringing communicating multiagent systems to the Web require ontologies. The integration of agent technology and ontologies could significantly affect the use of Web services and the ability to extend programs to perform tasks for users more efficiently and with less human intervention.
Toward Principles for the Design of Ontologies Used for Knowledge Sharing
- IN FORMAL ONTOLOGY IN CONCEPTUAL ANALYSIS AND KNOWLEDGE REPRESENTATION, KLUWER ACADEMIC PUBLISHERS, IN PRESS. SUBSTANTIAL REVISION OF PAPER PRESENTED AT THE INTERNATIONAL WORKSHOP ON FORMAL ONTOLOGY
, 1993
"... Recent work in Artificial Intelligence is exploring the use of formal ontologies as a way of specifying content-specific agreements for the sharing and reuse of knowledge among software entities. We take an engineering perspective on the development of such ontologies. Formal ontologies are viewed a ..."
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Cited by 2003 (3 self)
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Recent work in Artificial Intelligence is exploring the use of formal ontologies as a way of specifying content-specific agreements for the sharing and reuse of knowledge among software entities. We take an engineering perspective on the development of such ontologies. Formal ontologies are viewed as designed artifacts, formulated for specific purposes and evaluated against objective design criteria. We describe the role of ontologies in supporting knowledge sharing activities, and then present a set of criteria to guide the development of ontologies for these purposes. We show how these criteria are applied in case studies from the design of ontologies for engineering mathematics and bibliographic data. Selected design decisions are discussed, and alternative representation choices and evaluated against the design criteria.
Ontologies: Principles, methods and applications
- KNOWLEDGE ENGINEERING REVIEW
, 1996
"... This paper is intended to serve as a comprehensive introduction to the emerging field concerned with the design and use of ontologies. We observe that disparate backgrounds, languages, tools, and techniques are a major barrier to effective communication among people, organisations, and/or software s ..."
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Cited by 582 (3 self)
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This paper is intended to serve as a comprehensive introduction to the emerging field concerned with the design and use of ontologies. We observe that disparate backgrounds, languages, tools, and techniques are a major barrier to effective communication among people, organisations, and/or software systems. We show how the development and implementation of an explicit account of a shared understanding (i.e. an `ontology') in a given subject area, can improve such communication, which in turn, can give rise to greater reuse and sharing, inter-operability, and more reliable software. After motivating their need, we clarify just what ontologies are and what purposes they serve. We outline a methodology for developing and evaluating ontologies, first discussing informal techniques, concerning such issues as scoping, handling ambiguity, reaching agreement and producing de nitions. We then consider the bene ts of and describe, a more formal approach. We re-visit the scoping phase, and discuss the role of formal languages and techniques in the specification, implementation and evaluation of ontologies. Finally, we review the state of the art and practice in this emerging field,
Retrieving And Integrating Datafrom Multiple Information Sources
, 1993
"... With the current explosion of data, retrieving and integrating information from various sources is a critical problem. Work in multidatabase systems has begun to address this problem, but it has primarily focused on methods for communicating between databases and requires significant effort for e ..."
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Cited by 332 (31 self)
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With the current explosion of data, retrieving and integrating information from various sources is a critical problem. Work in multidatabase systems has begun to address this problem, but it has primarily focused on methods for communicating between databases and requires significant effort for each new database added to the system. This paper describes a more general approach that exploits a semantic model of a problem domain to integrate the information from various information sources. The information sources handled include both databases and knowledge bases, and other information sources (e.g., programs) could potentially be incorporated into the system. This paper describes how both the domain and the information sources are modeled, shows how a query at the domain level is mapped into a set of queries to individual information sources, and presents algorithms for automatically improving the efficiency of queries using knowledge about both the domain and the informat...
What makes patterns interesting in knowledge discovery systems
- IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
, 1996
"... One of the central problems in the eld of knowledge discovery is the development ofgood measures of interestingness of discovered patterns. Such measures of interestingness are divided into objective measures -- those that depend only on the structure of a pattern and the underlying data used in the ..."
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Cited by 276 (13 self)
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One of the central problems in the eld of knowledge discovery is the development ofgood measures of interestingness of discovered patterns. Such measures of interestingness are divided into objective measures -- those that depend only on the structure of a pattern and the underlying data used in the discovery process, and the subjective measures -- those that also depend on the class of users who examine the pattern. The focus of this paper is on studying subjective measures of interestingness. These measures are classified into actionable and unexpected, and the relationship between them is examined. The unexpected measure of interestingness is defined in terms of the belief system that the user has. Interestingness of a pattern is expressed in terms of how it affects the belief system. The paper also discusses how this unexpected measure of interestingness can be used in the discovery process.
Query Reformulation for Dynamic Information Integration
- JOURNAL OF INTELLIGENT INFORMATION SYSTEMS
, 1996
"... The standard approach to integrating heterogeneous information sources is to build a global schema that relates all of the information in the different sources, and to pose queries directly against it. The problem is that schema integration is usually difficult, and as soon as any of the information ..."
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Cited by 274 (32 self)
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The standard approach to integrating heterogeneous information sources is to build a global schema that relates all of the information in the different sources, and to pose queries directly against it. The problem is that schema integration is usually difficult, and as soon as any of the information sources change or a new source is added, the process mayhave to be repeated. The SIMS system uses an alternative approach. A domain model of the application domain is created, establishing a fixed vocabulary for describing data sets in the domain. Using this language, each available information source is described. Queries to SIMS against the collection of available information sources are posed using terms from the domain model, and reformulation operators are employed to dynamically select an appropriate set of information sources and to determine how to integrate the available information to satisfy a query. This approach results in a system that is more flexible than existing ones, more easily scalable, and able to respond dynamically to newly available or unexpectedly missing information sources.
OIL: An Ontology Infrastructure for the Semantic Web
- IEEE Intelligent Systems
, 2001
"... Researchers in artificial intelligence first developed ontologies to facilitate knowledge sharing and reuse. Since the beginning of the 1990s, ontologies have become a popular research topic, and several AI research communities—including Ontologies play a major role in supporting information exchang ..."
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Cited by 268 (32 self)
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Researchers in artificial intelligence first developed ontologies to facilitate knowledge sharing and reuse. Since the beginning of the 1990s, ontologies have become a popular research topic, and several AI research communities—including Ontologies play a major role in supporting information exchange across various networks. A prerequisite for such a role is the development of a joint standard for specifying and exchanging ontologies. The authors present OIL, a proposal for
Introduction to the special issue on word sense disambiguation
- Computational Linguistics J
, 1998
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