this article.

The eXtensible Markup Language (XML) is fast emerging as the dominant standard for describing and interchanging data among various systems and databases on the Internet. It offers the Document Type Definition (DTD) as a formalism for defining the syntax and structure of XML documents. The XML Schema definition language, as a replacement for the DTD, provides more rich facilities for defining and constraining the content of XML documents. However, it does not concentrate on the semantics that underlies these documents, representing a logical data model rather than a conceptual model. To enable efficient business application development in large-scale electronic commerce environments, it is necessary to describe and model real-world data semantics and their complex interrelationships. In this article, we describe a design methodology for XML documents. The aim is to enforce XML conceptual modeling power and bridge the gap between software development and XML document structures. The proposed methodology is comprised of two design levels: the semantic level and the schema level. The first level is based on a semantic network, which provides semantic modeling of XML through four major components: a set of atomic and complex nodes, representing real-world objects; a set of directed edges, representing semantic relationships between the objects; a set of labels denoting different types of semantic relationships, including aggregation, generalization, association, and of-property relationships; and finally a set of constraints defined over nodes and edges to constrain semantic relationships and object domains. The other level of the proposed methodology is concerned with detailed XML schema design, including element/attribute declarations and simple/complex type definitions. The mapping between the two design levels is proposed to transform the XML semantic model into the XML Schema, based on which XML documents can be systematically created, managed, and validated.

this paper, I will discuss two aspects of SNePS propositional semantic networks [5, 8, 12, 17] that distinguish them as formalisms for the representation of knowledge---cables and paths. I will also discuss a kind of inference sanctioned by each one---reduction inference and path-based inference, respectively, and the integration of these two kinds of inference into a kind of "subconscious" reasoning. Informally, a semantic network is a labelled directed acyclic graph in which nodes represent entities and labelled arcs represent binary relations between entities. A propositional semantic network is a semantic network in which every proposition represented in the network is represented by a node, rather than by an arc. We will refer to a node that represents a proposition as a propositional node. Isolated nodes are not allowed in a semantic network, and since a semantic network is a variety of relational graph, it does not make sense to have two arcs with the same label emanate from the same node and terminate at the same node. However, there is no restriction forbidding several arcs with the same label from emanating from the same node if they terminate in different nodes. Informally, we will call a set of such arcs a cable. (We will formalize this below.) A propositional node, therefore, may have a set of cables emanating from it. Each cable represents an argument position of the proposition represented by the propositional node, the label

We present a formal description of a logical language that is based on a propositional semantic network. Variables in this language are not atomic and have potentially complex structure. We start from the individual components of a semantic network system, atomic nodes and relations that connect nodes, and provide a complete specification for the structure of nodes and a subsumption procedure between nodes. We differ from other work in subsumption in that the representation language is uniform and based on an extended first-order predicate logic. The language is particularly suitable for addressing some problems associated with natural language processing, namely the representation of complex natural language descriptions and inference associated with description subsumption. 1 Introduction We present a formal description of a propositional semantic-network-based knowledge representation system. Variables in this representation are not atomic and have potentially complex structure. We...

What is the computational notion of "implementation"? It is not individuation, instantiation, reduction, or supervenience. It is, I suggest, semantic interpretation. This document is Technical Report 97-15 (Buffalo: SUNY Buffalo Department of Computer Science) and Technical Report 97-5 (Buffalo: SUNY Buffalo Center for Cognitive Science). 1 INTRODUCTION Consider the relationships among algorithms, computer programs, and the computers that execute them. An algorithm is (roughly) a procedure for computing a function (for more details, see Soare 1996; Rapaport, forthcoming). A program is a more specific and detailed textual expression of an algorithm, expressed in a programming language. Often, it is said that the program "implements" the algorithm. A computer process is an algorithm being executed (see Rapaport 1988, 1995; Smith 1997). It is a physical device (a computer) behaving in a certain way ; the way is described (or specified) by the program, and the physical device running the ...

We compare the formalism of minimal recursion semantics (MRS) with that of SNePS and conclude that scope-resolved MRS and SNePS are notational variants of each other. 1

SNePS is a representative semantic network. This paper shows suggestive evidence that SNePS model of information and SNePS path-based query language have similar features as current semi-structured data models and query languages. This leads us to conclude that SNePS is well-suited to deal with semi-structured data. We show some advantages and limitations of such use of SNePS.