Lehmann, F. (ed). 1992. Semantic Networks in Artificial Intelligence. Tarrytown, NY: Pergamon Press. Home/Search Document Not in Database Summary Related Articles Check |
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Experimental Comparison of Graph-Based Relational Concept .. - Gonzalez, Holder, Cook (2002) (Correct)
....converting graphs into the logic representation used by ILP systems. In section 4 we present some experiments that indicate the utility of using conceptual graphs for the comparison with ILP systems. Conceptual Graphs (CGs) are a logic based knowledge representation derived from semantic networks [7] and Peirce existential graphs [11] CGs are being used in different areas such as natural language processing, information retrieval and expert systems. Formally, a conceptual graph [11] G = R, C, U, lab) is a bipartite, connected, and finite graph. R and C are the relation and concept vertices ....
Lehmann, F. (1992). Semantics Networks in Artificial Intelligence. Oxford: Pergamon Press.
Linguistic Tool Based Information Elicitation in Large .. - Milliner, Papazoglou, .. (1996) (2 citations) (Correct)
....the ontological commitments of a set of participating databases. To achieve a logical sub division of the distributed information space, we arrange our database cluster space in a form that resembles a cluster based associative network [7] This type of network is a variant of semantic networks [8] which uses numerically weighted similarity links. In this way we can define cluster of nodes relevant to any given node by calculating weighted association links between the nodes, based on average of contextual closeness in several feature dimensions, including in the relevant cluster only ....
F. Lehmann (Ed) "Semantic Networks in Artificial Intelligence", Pergamon Press, 1992.
Conceptual Graphs are also Graphs - Chein, Mugnier (1995) (6 citations) (Correct)
....our research concerning theoretical and algorithmical aspects of the CG model. 2 The Formal Model 2.1 Descriptive Part A structure, we call a support, provides background knowledge on a specific domain application. It represents an ontology of this domain, as the T Box of terminological systems [Leh92]. It corresponds to the notion of a canon in [Sow84] A support consists of a 5 tuple S = T c ; T r ; oe; I ; where: T c is an ordered set not necessarily a lattice of concept types, with a supremum (the universal type) and an infimum (the absurd type) T r is an ordered ....
F. Lehmann, editor. Semantics Networks in Artificial Intelligence. Pergamon Press, 1992.
Nested Graphs: A Graph-based Knowledge Representation.. - Chein, Mugnier, Simonet (1998) (5 citations) (Correct)
....to the paper appeared in the KR 98 proceedings. It provides minor corrections. 1 Introduction Different kinds of labelled graphs have long been used for representing knowledge. In artificial intelligence, they have been investigated under the name of semantic networks (see for instance [Leh92] for an overview of recent research in this domain) Sow76] proposed a model of this family, named conceptual graphs (CGs) which was developed in [Sow84] The formal aspects of this model have two mathematical bases: logic and graph theory. Emphasizing one or the other leads to different ....
F. Lehmann, editor. Semantics Networks in Artificial Intelligence. Pergamon Press, 1992.
Using Conceptual Graphs To Represent Database Inference Security.. - Thomas (Correct)
....chosen for this research is that of conceptual graphs (Sowa, 1984; Nagle, Nagle, Gerholz, Eklund, 1992) Conceptual graphs are a graphically oriented notation based on first order logic as denoted by Charles Peirce s existential graphs from the late 1800 s. An extension of semantic networks (Lehmann, 1992), they provide a powerful, extensible means of capturing real world knowledge, such as the difference between class types and instances of a 6 Database Inference Conceptual Graphs class, multiple constraints on an individual or class and inheritance of type characteristics from a ....
Lehmann, F. (1992). Semantic Networks in Artificial Intelligence. Pergamon Press, Oxford.
Towards Object Visualization by Conceptual Graphs - Gogolla (1996) (Correct)
....tradition of approaches studying the relationship between conceptual graphs and object orientation [Sow93a, Sow93b, WG93, KFKD94, Ell95] We introduce an information system specification language based on the object oriented paradigm. Our approach also has close connections to semantic networks [Leh92] and database design, especially classical semantic data models [HK87, PM88] like the Entity Relationship model [Che76, Gog94] Our motivation for using conceptual graphs lies in the aim of gaining a better understanding of complex specifications by visualizing them. Such an approach is ....
F. Lehmann. Semantic Networks in Artificial Intelligence. Pergamon Press, Oxford, 1992.
Linguistic Tool Based Information Elicitation in Large .. - Milliner, Papazoglou, .. (1996) (2 citations) (Correct)
....the ontological commitments of a set of participating databases. To achieve a logical sub division of the distributed information space, we arrange our database cluster space in a form that resembles a cluster based associative network [7] This type of network is a variant of semantic networks [8] which uses numerically weighted similarity links. In this way we can define cluster of nodes relevant to any given node by calculating weighted association links between the nodes, based on average of contextual closeness in several feature dimensions, including in the relevant cluster only ....
F. Lehmann (Ed) "Semantic Networks in Artificial Intelligence", Pergamon Press, 1992.
A Unified Framework for Class-Based Representation.. - Calvanese, Lenzerini, Nardi (1994) (38 citations) (Correct)
....a subclass of another class, and more generally, whether a given constraint holds between two classes. Three main families of class based formalisms can be identified. The first one comes from knowledge representation and in particular from the work on semantic networks and frames (see for example [Leh92, Sow91]) The second one originates in the field of databases and in particular from the work on semantic data models (see for example [HK87] The third one arises from the work on types in programming languages and object oriented systems (see for example [KL89] In the past there have been several ....
Fritz Lehmann, editor. Semantic Networks in Artificial Intelligence. Pergamon Press, Oxford, 1992.
Under consideration for publication in Knowledge and.. - Systems Editorial Ontology (Correct)
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Lehmann, F. (ed). 1992. Semantic Networks in Artificial Intelligence. Tarrytown, NY: Pergamon Press.
An Upper-Level Ontology for the Biomedical Domain - McCray (2003) (1 citation) (Correct)
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Lehmann F. 1992. Semantic Networks in Artificial Intelligence. Pergamon: Tarrytown, New York.
Interests and Background Relevant - To Self-Aware Computer (Correct)
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F. Lehmann, editor. Semantic Networks in Artificial Intelligence. Pergamon Press, Oxford, 1992.
A Contextual-Logic Framework Based on Relational Power Context.. - Groh (2002) (Correct)
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F. Lehmann, editor. Semantic Networks in Artificial Intelligence. Pergamon Press, Oxford, 1992.
Navigation in Object-Oriented Reverse Engineering - Schweizer (2002) (1 citation) (Correct)
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F. Lehmann and E. Y. Rodin. Semantic Networks in Artificial Intelligence. Pergamon Press, 1992. (p 13)
Preferential Ordering Of Beliefs For - Default Reasoning By (Correct)
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Fritz Lehmann (ed.), Semantic networks in artificial intelligence, Pergamon Press, Oxford, 1992.
Integrating a Part Relationship into an Open OODB.. - Halper, Geller, Perl.. (1994) (9 citations) (Correct)
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F. Lehmann, editor. Semantic Networks in Artificial Intelligence. Pergamon Press, Tarrytown, NY, 1992.
Implementing Integrity Constraints in an Existing Belief.. - Johnson, Shapiro (2000) (Correct)
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Lehmann, F., ed. 1992. Semantic Networks in Artificial Intelligence. Oxford: Pergamon Press.
Automatic Belief Revision in SNePS - Stuart Shapiro And (2000) (Correct)
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Lehmann, F., ed. 1992. Semantic Networks in Artificial Intelligence. Oxford: Pergamon Press.
Our Dinner with Cassie - Shapiro, Ismail, Santore (2000) (Correct)
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Lehmann, F., ed. 1992. Semantic Networks in Artificial Intelligence. Oxford: Pergamon Press.
A Fully Formalized Theory for Describing Visual Notations.. - Haarslev (1996) (9 citations) (Correct)
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F. Lehmann, Ed., Semantic Networks in Artificial Intelligence, Pergamon Press, Oxford, England, 1992.
Integrating a Part Relationship into an Open OODB.. - Halper, Geller, Perl.. (1994) (9 citations) (Correct)
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F. Lehmann, editor. Semantic Networks in Artificial Intelligence. Pergamon Press, Tarrytown, NY, 1992.
SNePS: A Logic for Natural Language Understanding and Commonsense .. - Shapiro (1999) (2 citations) (Correct)
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Lehmann, F., editor (1992). Semantic Networks in Artificial Intelligence. Pergamon Press, Oxford.
Logics for Databases and Information Systems - Jan Chomicki, Gunter Saake (Eds.) (1998) (15 citations) (Correct)
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Fritz Lehmann, editor. Semantic Networks in Artificial Intelligence. Pergamon Press, Oxford, 1992.
Embodied Cassie - Shapiro (1998) (1 citation) (Correct)
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Lehmann, F., ed. 1992. Semantic Networks in Artificial Intelligence. Oxford: Pergamon Press.
The CORALI Project: From Conceptual Graphs to Conceptual Graphs.. - Chein (1997) (4 citations) (Correct)
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#F. Lehmann (edt). Semantic Networks in Artificial Intelligence. Pergamon, 1992.
Formalizing English - Shapiro (1996) (1 citation) (Correct)
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Lehmann, F., editor (1992). Semantic Networks in Artificial Intelligence. Pergamon Press, Oxford.
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