Sowa, J.F. (2000). "Knowledge Representation: Logical, Philosophical, and Computational Foundations." Brooks Cole Publishing Co., Pacific Grove, CA. pp. 492, 497 et seq.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....schemas when needed [Matt88] and (3) They facilitate automated schema design tools that help the designers to develop, verify, validate and implement conceptual schemas [Stor93] In broad domains, there are many generic relationship types. The top level categories of general ontologies [Cyco97, Sowa00] include many of them. If the conceptual schema for a particular domain is embedded within a general ontology, then many domain specific relationship types are realizations of generic ones. Given the benefits, some authors recommend that all relationship types should be defined as realizations of ....

Sowa, J. "Knowledge Representation. Logical, Philosophical and Computational Foundations", Brooks/Cole, 594 p.

....and a global context. Van Dijk (1998) gives a good example in the analysis of political discourses. In computer aware applications, the system Fisheye do a similar operation [Pook, 2000] However, this approach is not new: Conceptual graphs already proposes mechanisms of aggregation and expansion [Sowa, 2000]) Nevertheless, context must be represented in machine in an efficient way for modeling knowledge and reasoning, from the programming point of view as well as the viewpoint of its effective use. 3.5 The object of the context induces different contexts An explicit use of the context may bring ....

Sowa, J.F., "Knowledge Representation: Logical, Philosophical, and Computational Foundations", Brooks Cole Publishing Co., Pacific Grove, CA, 2000.

....and measures are tuned to improve the dis covering of knowledge in texts. 3. Conceptual graphs To compare two texts, e.g. a document and the user s query, first their representations in the form of conceptual graphs are built. A conceptual graph is a network of concept nodes and relation nodes [10, 11]. The concept nodes represent entities, attributes, or events (actions) they are denoted with brackets. The relation nodes identify the kind of relationship between two concept nodes; they are denoted with parentheses. At present, we consider relations from a few basic types, such as attribute, ....

Sowa, John F. (1999). "Knowledge Representation: Logical, Philosophical and Computational Foundations". 1 edition, Thomson Learning, 1999.

....just keywords, i.e. representations with more types of textual elements. Under this circumstance, it is necessary to have the appropriate methods for the comparison of two texts in any of these new representations. In this paper, we consider the representation of the texts by conceptual graphs [9,10] and focus on the design of a method for comparison of two conceptual graphs. This is a continuation of the research reported in [15] Most methods for comparison of conceptual graphs come from information retrieval research. Some of them are restricted to the problem of determining if a graph, ....

....in subsection 3.2. An illustrative example is shown in section 4, and finally, some conclusions are discussed in the section 5. 2. Conceptual Graphs This section introduces well known notions and facts about conceptual graphs. A conceptual graph is a finite oriented connected bipartite graph [9,10]. The two different kinds of nodes of this bipartite graph are concepts and relations. Concepts represent entities, actions, and attributes. Concept nodes have two attributes: type and referent. Type indicates the class of the element represented by the concept. Referent indicates the specific ....

Sowa, John F. (1999). "Knowledge Representation: Logical, Philosophical and Computational Foundations". 1st edition, Thomson Learning, 1999.

....logic [9] nature being an uninterpreted logic. The logic doesn t impose any constraint on the subject of its interest or on the way it should be predicated. The use of this logic in combination with ontology, such as the one that RM ODP presents, is justified by different authors (see for example [35]) Second, to consider model elements being destitute of complexity is consistent with Russell s theory of types [32] Third, by considering all the model elements as having the object s properties we exclude the possibility of having in the model those basic modelling concepts that ....

J. F. Sowa. "Knowledge Representation: Logical, Philosophical, and Computational Foundations", Brooks/Cole, 2000.

....and the XML based document retrieval, mapping and storage. An ontology is an explicit (possibly formal) specification of the names for referring to the objects in the application and the (logical) statements that describe what these objects are, and how they are related or not to each other [10, 16 17, 20]. Ontology therefore provides a vocabulary for representing and communicating knowledge that can exist for an agent or a community of agents, for the purpose of enabling knowledge sharing and reuse. The socalled ontological commitment means an agreement to use a vocabulary (i.e. for queries) in a ....

J. F. Sowa, "Knowledge Representation: Logical, Philosophical, and Computational Foundations", Brooks Cole Publishing Co., Pacific Grove, 1999

....equivalents of frame predicates, which indicate that the relation given as the first argument holds between the instance given as the second argument and N instances of the class specified in the third argument where N is the fourth argument. This statement is equivalent to (following notation in [Sowa, 1999]) x:arg3) x arg4arg1(arg2,x) Constant: BlueMechBgd1. in Mt: BlueDivisionCOA1 1Mt. F: isa BlueMechBgd1 MechanizedInfantryUnit MilitarySpecialty) F: isa BlueMechBgd1 ArmoredUnit MilitarySpecialty) F: echelonOfUnit BlueMechBgd1 Brigade UnitDesignation) F: sovereignAllegianceOfOrg ....

Sowa, 1999, "Knowledge Representation: Logical, Philosophical and Computational Foundations", Brooks/Cole pub.

....Social; this theory also specializes strata according to some scientific granularities [3] The basic intuition is that reality (in the most neutral way we could figure it out) is layered , and such layers have a complex inter dependence. Theory: granularity implements Sowa s adaptation [36] of Searle s ontology of intentionality [34] which makes a fundamental distinction between epistemic and ontological facts, also recognizing an intentional level which pertains (mainly) to the semiotic aspects of the description of the world in the human (or another organism s) form ....

....located, a domain in which this state of affairs may occur, a time span of occurrence, etc. 4) applied formal ontology theories: meronymy, theory of positions, time theories. There are three different ontologies of time in this library: a) thetemporal mereology [1] see also an adaptation in [36]) uses mereological concepts in its definitions; its relations apply directly to intervals, thus it is difficult to state the common sense notion by which we talk of processes and situations as intrinsically intervallistic. Anyway, the basic ideas in all these theories are founded on some version ....

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Sowa J, "Knowledge Representation: Logical, Philosophical and Computational Foundations", Boston, PWS, in press.

....Psychological, Social, Abstract; this theory also specializes strata according to some scientific granularities [4] Atomic, Molecular, etc. The basic intuition is that reality is layered , and the layers have a complex inter dependence. Theory: granularity implements Sowa s adaptation [52] of Searle s ontology of intentionality [50] which makes a fundamental distinction between epistemic and actual identity. For example, a surgical knife has an actual identity described by its form, material, color, etc. and an epistemic identity given by the building and measuring ....

....is a pathological process, but it causes a physical modification involving the change of a morphological property: an organ becomes inflamed . There are three different ontologies of time in our library: Temporal mereology (originally formulated by Allen [1] see also an adaptation in [52]) uses mereological concepts in its definitions; its relations apply directly to intervals. Unrestricted time aims at representing the common sense metonymy by which we use temporal relations ranging over processes and situations rather than intervals. It also defines Kamp s parallel time lines ....

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Sowa J, "Knowledge Representation: Logical, Philosophical and Computational Foundations", Boston, PWS, in press.

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Sowa, J.F. (2000). "Knowledge Representation: Logical, Philosophical, and Computational Foundations." Brooks Cole Publishing Co., Pacific Grove, CA. pp. 492, 497 et seq.

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John F. Sowa. Knowledge Representation: Logical Philosophical, and Computational Foundations. Brooks Cole Publishing Co, Pacific Grove, CA, 2000.

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John F. Sowa. Knowledge Representation: Logical Philosophical, and Computational Foundations. Brooks Cole Publishing Co, Pacific Grove, CA, 2000.

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Sowa, John F. "Knowledge Representation: Logical, Philosophical, and Computational Foundations", Brooks Cole Publishing Co., Pacific Grove, CA, 2000.

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John F. Sowa. Knowledge Representation: Logical Philosophical, and Computational Foundations. PWS Publishers, 1996.

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