-
Trost, H.: Begriffsbildung im Bereich natürlichsprachiger Systeme (1989)
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- Source
- 5. Österreichische Artificial Intelligence Tagung. Hrsg.: J. Retti u. K. Leidlmair
-
Jouis, C.: Logic of relationships (2002)
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- Abstract
- A main goal of recent studies in semantics is to integrate into conceptual structures the models of representation used in linguistics, logic, and/or artificial intelligence. A fundamental problem resides in the need to structure knowledge and then to check the validity of constructed representations. We propose associating logical properties with relationships by introducing the relationships into a typed and functional system of specifcations. This makes it possible to compare conceptual representations against the relationships established between the concepts. The mandatory condition to validate such a conceptual representation is consistency. The semantic system proposed is based an a structured set of semantic primitives-types, relations, and properties-based an a global model of language processing, Applicative and Cognitive Grammar (ACG) (Desc16s, 1990), and an extension of this model to terminology (Jouis & Mustafa 1995, 1996, 1997). The ACG postulates three levels of representation of languages, including a cognitive level. At this level, the meanings of lexical predicates are represented by semantic cognitive schemes. From this perspective, we propose a set of semantic concepts, which defines an organized system of meanings. Relations are part of a specification network based an a general terminological scheure (i.e., a coherent system of meanings of relations). In such a system, a specific relation may be characterized as to its: (1) functional type (the semantic type of arguments of the relation); (2) algebraic properties (reflexivity, symmetry, transitivity, etc.); and (3) combinatorial relations with other entities in the same context (for instance, the part of the text where a concept is defined).
- Date
- 1.12.2002 11:12:22
-
Sowa, J.F.: Top-level ontological categories (1995)
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- Abstract
- Surveys ontological questions that arise in artificial intelligence, some of the answers that have been proposed by various philosophers, and an application of the philosophical analysis to the clarification of some current issues in artificial intelligence. Charles Sanders Peirce and Alfred North Whitehead have developed the most complete systems of categories. Their analyses suggest a basic structure of categories that can provide some guidelines for the design of artificial intelligence systems
-
Harras, G.: Concepts in linguistics : concepts in natural language (2000)
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- Series
- Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
-
Dahlberg, I.: ¬Die gegenstandsbezogene, analytische Begriffstheorie und ihre Definitionsarten (1987)
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- Pages
- S.9-22
-
Gerbé, O.; Mineau, G.W.; Keller, R.K.: Conceptual graphs, metamodelling, and notation of concepts : fundamental issues (2000)
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- Series
- Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
-
Pribbenow, S.: Meronymic relationships : from classical mereology to complex part-whole relations (2002)
0.02
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- Abstract
- Meronymic or partonomic relations are ontological relations that are considered as fundamental as the ubiquitous, taxonomic subsumption relationship. While the latter is well-established and thoroughly investigated, there is still much work to be done in the field of meronymic relations. The aim of this chapter is to provide an overview an current research in characterizing, formalizing, classifying, and processing meronymic or partonomic relations (also called part-whole relations in artificial intelligence and application domains). The first part of the chapter investigates the role of knowledge about parts in human cognition, for example, visual perception and conceptual knowledge. The second part describes the classical approach provided by formal mereology and its extensions, which use one single transitive part-of relation, thus focusing an the notion of "part" and neglecting the notion of (something being a) "whole". This limitation leads to classifications of different part-whole relations, one of which is presented in the last part of the chapter.
-
Wüster, E.: Begriffs- und Themaklassifikation : Unterschiede in ihrem Wesen und in ihrer Anwendung (1971)
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- Source
- Nachrichten für Dokumentation. 22(1971) H.3, S.98-104 (T.1); H.4, S.143-150 (T.2)
-
Sowa, J.F.: Ontology, metadata, and semiotics (2000)
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- Series
- Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
-
Barsalou, L.W.: Frames, concepts, and conceptual fields (1992)
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- Abstract
- In this chapter I propose that frames provide the fundamental representation of knowledge in human cognition. In the first section, I raise problems with the feature list representations often found in theories of knowledge, and I sketch the solutions that frames provide to them. In the second section, I examine the three fundamental concepts of frames: attribute-value sets, structural invariants, and constraints. Because frames also represents the attributes, values, structural invariants, and constraints within a frame, the mechanism that constructs frames builds them recursively. The frame theory I propose borrows heavily from previous frame theories, although its collection of representational components is somewhat unique. Furthermore, frame theorists generally assume that frames are rigid configurations of independent attributes, whereas I propose that frames are dynamic relational structures whose form is flexible and context dependent. In the third section, I illustrate how frames support a wide variety of representational tasks central to conceptual processing in natural and artificial intelligence. Frames can represent exemplars and propositions, prototypes and membership, subordinates and taxonomies. Frames can also represent conceptual combinations, event sequences, rules, and plans. In the fourth section, I show how frames define the extent of conceptual fields and how they provide a powerful productive mechanism for generating specific concepts within a field.
-
Dahlberg, I.: Begriffsarbeit in der Wissensorganisation (2010)
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- Source
- Wissensspeicher in digitalen Räumen: Nachhaltigkeit - Verfügbarkeit - semantische Interoperabilität. Proceedings der 11. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation, Konstanz, 20. bis 22. Februar 2008. Hrsg.: J. Sieglerschmidt u. H.P.Ohly
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Storms, G.; VanMechelen, I.; DeBoeck, P.: Structural-analysis of the intension and extension of semantic concepts (1994)
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- Date
- 22. 7.2000 19:17:40
-
Bauer, G.: ¬Die vielseitigen Anwendungsmöglichkeiten des Kategorienprinzips bei der Wissensorganisation (2006)
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- Pages
- S.22-33
-
Conceptual structures : logical, linguistic, and computational issues. 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000 (2000)
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- Series
- Lecture notes in computer science; vol.1867: Lecture notes on artificial intelligence
-
Treude, L.: ¬Das Problem der Konzeptdefinition in der Wissensorganisation : über einen missglückten Versuch der Klärung (2013)
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- Source
- LIBREAS: Library ideas. no.22, 2013, S.xx-xx
-
Marradi, A.: ¬The concept of concept : concepts and terms (2012)
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- Date
- 22. 1.2012 13:11:25
-
Besler, G.; Szulc, J.: Gottlob Frege's theory of definition as useful tool for knowledge organization : definition of 'context' - case study (2014)
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- Source
- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
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Olson, H.A.: How we construct subjects : a feminist analysis (2007)
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- Date
- 11.12.2019 19:00:22
