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Formal Ontology and Information Systems
, 1998
"... Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We sh ..."
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Cited by 878 (11 self)
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Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We shall use the generic term information systems, in its broadest sense, to collectively refer to these application perspectives. We argue in this paper that so-called ontologies present their own methodological and architectural peculiarities: on the methodological side, their main peculiarity is the adoption of a highly interdisciplinary approach, while on the architectural side the most interesting aspect is the centrality of the role they can play in an information system, leading to the perspective of ontology-driven information systems.
Advertising as Information
- Journal of Political Economy
, 1974
"... for a R+D+I Centre to organize, retrieve and share ..."
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Cited by 484 (0 self)
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for a R+D+I Centre to organize, retrieve and share
Ontologies and knowledge bases: Towards a terminological clarification
- Towards very Large Knowledge bases: Knowledge Building and Knowledge sharing
, 1995
"... The word “ontology ” has recently gained a good popularity within the knowledge engineering community. However, its meaning tends to remain a bit vague, as the term is used in very different ways. Limiting our attention to the various proposals made in the current debate in AI, we isolate a number o ..."
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Cited by 305 (13 self)
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The word “ontology ” has recently gained a good popularity within the knowledge engineering community. However, its meaning tends to remain a bit vague, as the term is used in very different ways. Limiting our attention to the various proposals made in the current debate in AI, we isolate a number of interpretations, which in our opinion deserve a suitable clarification. We elucidate the implications of such various interpretations, arguing for the need of clear terminological choices regarding the technical use of terms like “ontology”, “conceptualization ” and “ontological commitment”. After some comments on the use “Ontology ” (with the capital “o”) as a term which denotes a philosophical discipline, we analyse the possible confusion between an ontology intended as a particular conceptual framework at the knowledge level and an ontology intended as a concrete artifact at the symbol level, to be used for a given purpose. A crucial point in this clarification effort is the careful analysis of Gruber’ s definition of an ontology as a specification of a conceptualization. 1
Ontology-Based Integration of Information - A Survey of Existing Approaches
, 2001
"... We review the use on ontologies for the integration of heterogeneous information sources. Based on an in-depth evaluation of existing approaches to this problem we discuss how ontologies are used to support the integration task. We evaluate and compare the languages used to represent the ontologies ..."
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Cited by 285 (2 self)
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We review the use on ontologies for the integration of heterogeneous information sources. Based on an in-depth evaluation of existing approaches to this problem we discuss how ontologies are used to support the integration task. We evaluate and compare the languages used to represent the ontologies and the use of mappings between ontologies as well as to connect ontologies with information sources. We also enquire into ontology engineering methods and tools used to develop ontologies for information integration. Based on the results of our analysis we summarize the state-of-the-art in ontology-based information integration and name areas of further research activities.
OilEd: a Reason-able Ontology Editor for the Semantic Web
- Proceedings of KI2001, Joint German/Austrian conference on Artificial Intelligence
, 2001
"... Ontologies will play a pivotal r61e in the "Semantic Web", where they will provide a source of precisely defined terms that can be communicated across people and applications. OilEd, is an ontology editor that has an easy to use fi'ame interface, yet at the same time allows users ..."
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Cited by 240 (32 self)
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Ontologies will play a pivotal r61e in the "Semantic Web", where they will provide a source of precisely defined terms that can be communicated across people and applications. OilEd, is an ontology editor that has an easy to use fi'ame interface, yet at the same time allows users to exploit the full power of an expressive web ontology language (OIL). OilEd uses reasoning to support ontology design, facilitating the development of ontologies that are both more detailed and more accurate.
Towards a Methodology for Building Ontologies
- In Workshop on Basic Ontological Issues in Knowledge Sharing, held in conjunction with IJCAI-95
, 1995
"... We outline some requirements for a comprehensive methodology for building ontologies, and review some important work that has been done in the area which could contribute to this goal. We describe our own experiences in constructing a significant ontology, emphasising the ontology capture phase. We ..."
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Cited by 240 (4 self)
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We outline some requirements for a comprehensive methodology for building ontologies, and review some important work that has been done in the area which could contribute to this goal. We describe our own experiences in constructing a significant ontology, emphasising the ontology capture phase. We first consider the very general issue of categorisation in modelling, and relate it to the process of ontology capture. We then describe the procedure that we used to identify the terms and produce definitions. We describe a successful way to handle ambiguous terms, which can be an enormous obstacle to reaching a shared understanding. Other important findings include: it may not be necessary to identify competency questions before building the ontology; the meta-ontology can be chosen after detailed text definitions are produced; defining terms which are 'cognitively basic' first can lead to less re-work. AIAI-TR-183 Page 1 of 13 1 Introduction Currently, a considerable body of experience...
Formal Ontology, Conceptual Analysis and Knowledge Representation
- INTERNATIONAL JOURNAL OF HUMAN AND COMPUTER STUDIES
, 1995
"... The purpose of this paper is to defend the systematic introduction of formal ontological principles in the current practice of knowledge engineering, to explore the various relationships between ontology and knowledge representation, and to present the recent trends in this promising research area. ..."
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Cited by 227 (13 self)
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The purpose of this paper is to defend the systematic introduction of formal ontological principles in the current practice of knowledge engineering, to explore the various relationships between ontology and knowledge representation, and to present the recent trends in this promising research area. According to the "modelling view" of knowledge acquisition proposed by Clancey, the modeling activity must establish a correspondence between a knowledge base and two separate subsystems: the agent's behavior (i.e. the problem-solving expertize) and its own environment (the problem domain). Current knowledge modelling methodologies tend to focus on the former subsystem only, viewing domain knowledge as strongly dependent on the particular task at hand: in fact, AI researchers seem to have been much more interested in the nature of reasoning rather than in the nature of the real world. Recently, however, the potential value of task-independent knowlege bases (or "ontologies") suitable to large scale integration has been underlined in many ways. In this paper, we compare the dichotomy between reasoning and representation to the philosophical distinction between epistemology and ontology. We introduce the notion of the ontological level, intermediate between the epistemological and the conceptual level discussed by Brachman, as a way to characterize a knowledge representation formalism taking into account the intended meaning of its primitives. We then discuss some formal ontological distinctions which may play an important role for such purpose.
Description Logics as Ontology Languages for the Semantic Web
- Festschrift in honor of Jörg Siekmann, Lecture Notes in Artificial Intelligence
, 2003
"... The vision of a Semantic Web has recently drawn considerable attention, both from academia and industry. Description logics are often named as one of the tools that can support the Semantic Web and thus help to make this vision reality. ..."
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Cited by 182 (5 self)
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The vision of a Semantic Web has recently drawn considerable attention, both from academia and industry. Description logics are often named as one of the tools that can support the Semantic Web and thus help to make this vision reality.
A unifying reference framework for multi-target user interfaces
- INTERACTING WITH COMPUTERS
, 2003
"... ..."
Word sense disambiguation: a survey
- ACM COMPUTING SURVEYS
, 2009
"... Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence. We introduce the reader to the ..."
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Cited by 170 (17 self)
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Word sense disambiguation (WSD) is the ability to identify the meaning of words in context in a computational manner. WSD is considered an AI-complete problem, that is, a task whose solution is at least as hard as the most difficult problems in artificial intelligence. We introduce the reader to the motivations for solving the ambiguity of words and provide a description of the task. We overview supervised, unsupervised, and knowledge-based approaches. The assessment of WSD systems is discussed in the context of the Senseval/Semeval campaigns, aiming at the objective evaluation of systems participating in several different disambiguation tasks. Finally, applications, open problems, and future directions are discussed.
