By Dan Corbett
Reasoning and Unification over Conceptual Graphs is an exploration of computerized reasoning and backbone within the increasing box of Conceptual buildings. Designed not just for computing scientists discovering Conceptual Graphs, but in addition for a person attracted to exploring the layout of information bases, the publication explores what are proving to be the elemental equipment for representing semantic relatives in wisdom bases. whereas it presents the 1st complete remedy of Conceptual Graph unification and reasoning, the publication additionally addresses primary problems with graph matching, computerized reasoning, wisdom bases, constraints, ontology and layout. With numerous examples, illustrations, and either formal and casual definitions and discussions, this publication is great as an educational for the reader new to Conceptual Graphs, or as a reference ebook for a senior researcher in synthetic Intelligence, wisdom illustration or computerized Reasoning.
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Additional resources for Reasoning and Unification over Conceptual Graphs
In order to avoid confusion in the system described here on interval constraints, we disallow the interval [x, y] where x > y. Older avoids defining the top and bottom of the lattice, in order to avoid "failure interpretations" in his algorithms. Failure interpretations in Older's system result from defining boundaries on the reals. Older chooses not to represent preset boundaries, but rather allows the lattice of the real intervals to be infinite [Older 1997]. 2 An Interval Concept Type Hierarchy It is possible to apply the idea of interval constraints to Conceptual Graphs.
In fact, Muller's entire definition and use of unification is as a method for logical resolution [Muller 1997]. While the application of Muller's head node was originally for a different purpose, the sense used by Muller can still be used for general unification for knowledge conjunction. 3 The Projection Operator The next step in defining constraints on concept markers is to define a projection operator, similar to Sowa's 1t operator [Sowa 1984], but which takes intervals into consideration. Sowa's 1t operator is used to identify that portion of a graph which is derived (by a join) from another graph.
Two of these fonns are shown here in Figure 9 and Figure 10, which are taken directly from Carpenter [Carpenter 1992]. Figure 10 illustrates the standard graphical notation for feature structures, where its automatalike and graph-like character are most apparent. The nodes are enclosed in small, numbered circles, and a small arrow indicates the root node. The type of each node appears in bold face next to their nodes, and the features label the arcs. Figure 9 illustrates the knowledge of a certain domain.