This article presents an experiment of expertise capitalization in road traffic-accident analysis. We study the integration of models of expertise from different members of an organization into a coherent corporate expertise model. We present our elicitation protocol and the generic models and tools we exploited for knowledge modeling in this context of multiple experts. Finally, we discuss the results of our experiment from a knowledge capitalization viewpoint.

This article presents an experiment of expertise capitalization in road traffic-accident analysis. We study the integration of models of expertise from different members of an organization into a coherent corporate expertise model. We present our elicitation protocol and the generic models and tools we exploited for knowledge modeling in this context of multiple experts. We compare the knowledge models obtained for seven experts in accidentology and their representation through conceptual graphs. Finally, we discuss the results of our experiment from a knowledge capitalization viewpoint.

To remain competitive, enterprises must become increasingly agile and integrated across their functions. Enterprise models play a critical role in this integration, enabling better designs for enterprises, analysis of their performance, and management of their operations. This article motivates the need for enterprise models and introduces the concepts of generic and deductive enterprise models. It reviews research to date on enterprise modeling and considers in detail the Toronto virtual enterprise effort at the University of Toronto.

We have selected 10 specific projects for this study, including general ontologies, domain-specific ones, and one knowledge representation system. The comparison framework includes general characteristics, such as the purpose of an ontology, its coverage (general or domain specific), its size, and the formalism used. Characteristics that describe the content of an ontology include taxonomic organization, types of concept covered, top-level divisions, internal structure of concepts, representation of part-whole relations, and the presence and nature of additional axioms. By identifying the similarities and differences among existing ontologies, we clarify the range of alternatives in creating a standard framework for ontology design.

In this article, we develop a framework for comparing ontologies and place a number of the more prominent ontologies into it. We have selected 10 specific projects for this study, including general ontologies, domain-specific ones, and one knowledge representation system. The comparison framework includes general characteristics, such as the purpose of an ontology, its coverage (general or domain specific), its size, and the formalism used. It also includes the design process used in creating an ontology and the methods used to evaluate it. Characteristics that describe the content of an ontology include taxonomic organization, types of concept covered, top-level divisions, internal structure of concepts, representation of part-whole relations, and the presence and nature of additional axioms. Finally, we consider what experiments or applications have used the ontologies. Knowledge sharing and reuse will require a common framework to support interoperability of independently created ontologies. Our study shows there is great diversity in the way ontologies are designed and the way they represent the world. By identifying the similarities and differences among existing ontologies, we clarify the range of alternatives in creating a standard framework for ontology design.

The Association for the Advancement of Artificial Intelligence (AAAI) held its 1997 Spring Symposium Series on 24 to 26 March at Stanford University in Stanford, California. This article contains summaries of the seven symposia that were conducted: (1) Artificial Intelligence in Knowledge Management; (2) Computational Models for Mixed-Initiative Interaction; (3) Cross-Language Text and Speech Retrieval; (4) Intelligent Integration and Use of Text, Image, Video, and Audio Corpora; (5) Natural Language Processing for the World Wide Web; (6) Ontological Engineering; and (7) Qualitative Preferences in Deliberation and Practical Reasoning.

This paper combines two important directions of research in temporal resoning: that of finding maximal tractable subclasses of Allen's interval algebra, and that of reasoning with metric temporal information. Eight new maximal tractable subclasses of Allen's interval algebra are presented, some of them subsuming previously reported tractable algebras. The algebras allow for metric temporal constraints on interval starting or ending points, using the recent framework of Horn DLRs. Two of the algebras can express the notion of sequentiality between intervals, being the first such algebras admitting both qualitative and metric time.

Most modern formalisms used in Databases and Artificial Intelligence for describing an application domain are based on the notions of class (or concept) and relationship among classes. One interesting feature of such formalisms is the possibility of defining a class, i.e., providing a set of properties that precisely characterize the instances of the class. Many recent articles point out that there are several ways of assigning a meaning to a class definition containing some sort of recursion. In this paper, we argue that, instead of choosing a single style of semantics, we achieve better results by adopting a formalism that allows for different semantics to coexist. We demonstrate the feasibility of our argument, by presenting a knowledge representation formalism, the description logic muALCQ, with the above characteristics. In addition to the constructs for conjunction, disjunction, negation, quantifiers, and qualified number restrictions, muALCQ includes special fixpoint constructs to express (suitably interpreted) recursive definitions. These constructs enable the usual frame-based descriptions to be combined with definitions of recursive data structures such as directed acyclic graphs, lists, streams, etc. We establish several properties of muALCQ, including the decidability and the computational complexity of reasoning, by formulating a correspondence with a particular modal logic of programs called the modal mu-calculus.

A workshop on defeasible reasoning with specificity was held under the arch in St. Louis during April 1989, with support from AAAI and McDonnell Douglas, and the assistance of Rockwell Science Center Palo Alto and the Department of Computer Science of Washington University.

A workshop on defeasible reasoning with specificity was held under the arch in St. Louis during April 1989, with support from AAAI and McDonnell Douglas, and the assistance of Rockwell Science Center Palo Alto and the Department of Computer Science of Washington University.