Robert M. MacGregor

Mermaid—A front-end to distributed heterogeneous databases

Mermaid is a system that allows the user of multiple databases stored under various relational DBMSs running on different machines to manipulate the data using a common language, either ARIEL or SQL. It makes the complexity of this distributed, heterogeneous data processing transparent to the user. In this paper, we describe the architecture, system control, user interface, language and schema translation, query optimization, and network operation of the Mermaid system. Future research issues are also addressed.

Inside the LOOM description classifier

This paper presents a symbol level account of some of the representation and reasoning structures within the LOOM knowledge representation system. Reasoning in LOOM centers around a classifier whose primary function is to construct a taxonomy of all descriptions that have been entered into the system. The LOOM classifier is unique in that it constructs a separate taxonomy for each of seven kinds of non-composite descriptions, and uses a marker passing algorithm to replace the quadratic time subsumption test found in most classifiers with a linear time test. We briefly illustrate how the selection of data structures within LOOM impacts the completeness of the classification algorithm, and we describe the LOOM option that allows concepts to be reasoned with in either a forward-chaining or a backward-chaining mode.

Building and (re)using an ontology of air campaign planning

This article presents a case study in building and (re)using an ontology in a specific application domain-air campaign planning. The article describes the common ontology built to serve as a basis for knowledge sharing and discusses several issues raised in its construction.

A subscribable peer-to-peer RDF repository for distributed metadata management

In this paper, we present a scalable peer-to-peer RDF repository, named RDFPeers, which stores each triple in a multi-attribute addressable network by applying globally known hash functions. Queries can be efficiently routed to the nodes that store matching triples. RDFPeers also enables users to selectively subscribe to RDF content. In RDFPeers, both the neighbors per node and the routing hops for triple insertion, most query resolution and triple subscription are logarithmic to the network size. Our experiments with real-world RDF data demonstrated that the triple-storing load among nodes differs by less than an order of magnitude.

Using a description classifier to enhance deductive inference

Descriptions are given of some of the emerging techniques and uses of classifier-based reasoning systems, specifically as they apply to the LOOM knowledge representation system. The author asserts that current generation expert system tools fail to achieve a satisfactory integration of frame knowledge and rule knowledge. He then describes a class of languages, exemplified by LOOM, that combine descriptions and rules to form a hybrid logic that does achieve a satisfactory level of integration. The use of classifier technology enables a form of unification over descriptions that fills a gap present in the frame-plus-rule (F+R) technology. In addition, classification-based inference technology is more powerful than the inference technology found in languages such as (pure) Prolog. A classifiers ability to automatically organize definitions and to detect many kinds of inconsistency can significantly benefit the task of knowledge acquisition. The unique capabilities of the classifier can be applied to enhance existing programming paradigms. The author highlights specific enhancements to the production rule and object-oriented programming paradigms.<<ETX>>

Term Subsumption Languages in Knowledge Representation

The Workshop on Term Subsumption Languages in Knowledge Representation was held 18-20 October 1989 at the Inn at Thorn Hill, located in the White Mountain region of New Hampshire.

CLASP: integrating term subsumption systems and production systems

The general architecture and an implementation of a classification-based production system (CLASP) are presented. The main objective is to extend the benefits of classification capabilities in frame systems to the developers of rule-based systems. Two major processes of CLASP, a semantic pattern matcher and a pattern classifier, are described. The semantic pattern matcher extends the pattern matching capabilities of rule-based systems through the use of terminological knowledge. The pattern classifier enables the system to compute a rules specificity, which is useful for conflict resolution, based on the semantics of its left-hand side. The paradigm not only enhances the reasoning capabilities of rule-based systems, but also helps to reduce the cost of maintaining such systems because definitional knowledge is explicitly represented in a form that facilitates sharing and minimizes duplication of effort. >

Using polymorphism to improve expert system maintainability

The problems encountered in applying object-oriented programming to expert systems are described. A production system called Clasp, which addresses these difficulties, is presented. Clasp integrates methods, production rules, and terminological definitions for classes. The approach is a further generalization of Common Loops and the Common Lisp Operating System, which have all extended notion of methods in which all argument types can describe the applicability of methods. The system was designed to improve the modularity and reusability of the rule base, to support the development of a more consistent and homogeneous knowledge base, and to enhance the predictability of rules.<<ETX>>

Representing reified relations in Loom

Abstract This paper discusses the semantics and usage of reification as applied to relations and tuples. The reification of a tuple is a proposition object possessing a case role for each domain attribute in the tuple. The reification of a set of fillers of a role is an object sometimes referred to as a ‘roleset’. In the course of defining reification mechanisms for the Loom knowledge representation system, we have unearthed several open issues that come into focus when considering equivalence relations between these kinds of reified objects. Another type of reification produces an individual that represents a view of another individual filling a particular role. We present a number of semantic variations of this reification operation, and argue that the unbridled application of such reification operators has the potential to overwhelm the representation mechanism. We suggest that a regimen that merges various similar but non-equivalent classes of individuals might be preferable to a system that insists o...