Carole D. Hafner

The State of the Art in Ontology Design: A Survey and Comparative Review

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.

Representing teleological structure in case-based legal reasoning: the missing link

We argue that robust case-based models of legal knowledge that represent the way in which practicing professionals use legal decisions must contain a deeper domain model that represents the purposes behind the rules articulated in the cases. We propose a model for representing the teleological components of legal decisions, and we suggest a method for utilizing this representation in a HYPO-like framework for case-based legal argument.

Conceptual organization of case law knowledge bases

Conceptual retrieval requires the computer to have knowledge of legal concepts and issues, and their relationship to the case law collection. This paper discusses the organization of a case law knowledge base in terms of three interacting components: a domain knowledge model defines the basic concepts of a case law domain; individual case descriptors describe the particular constellation of concepts that pertain to each case, organized into a frame-based superstructure according to the legal roles they fill; and issue/case discrimination trees represent the significance of each case relative to a model of the normative relationships of the legal domain. Each of these components is described and justified by showing its contribution to the goal of conceptual retrieval.

SmartLaw: adapting “classic” expert system techniques for the legal research domain

This report describes research in progress on the development of a computer expert system (SmartLaw) for giving advice on legal research problems. Legal research exhibits many of the characteristics of a suitable domain for expert system development; however, it also poses unique challenges for knowledge-based system design. To meet these challenges, we use a four-level knowledge structure of research STRATEGIES, GOALS, RESOURCES and PLANS, with three processing components: a rule-based backward-chaining reasoning component, a database component, and a hypertext component. This paper explains our evolving model of legal research knowledge and describes the architecture and implementation of a working prototype of the SmartLaw system.

Understanding precedents in a temporal context of evolving legal doctrine

In evaluating the precedential strength of a prior case, skilled attorneys take account of how the holdings of the case have been treated in subsequent decisions. This paper describes the process by which a formerly strong precedent may be weakened by over time, identifying five reasoning patterns by which attorneys may predict that a most-onpoint case is likely to be explicitly or implicitly overruled. We consider the requirements for implementing this form of analysis in a case-based legal reasoning system, proposing an extension to earlier schemes for case representation, and outlining an evidential reasoning algorithm to compute the degree to which the holdings of a prior case have been weakened.

Incorporating procedural context into a model of case-based legal reasoning

In this paper we analyze the procedural considerations that affect the use of legal casesas precedents and propose a model of procedural knowledge that can be combined with substantive legal reasoning models to produce a more robust theory of case-based legal reasoning in common law jurisdictions. Our model addresses one component of procedural knowledge the distinction between questions of fact and questions of law. We categorize 32 different procedural scenarios into 10 basic types of legal results. We then propose rules for determining the precedential value of these result types. Finally we suggest a method for incorporating procedural distinctions into case-based reasoning systems.

Ontological foundations for experimental science knowledge bases

The framework for representing domain ontologies presented in this paper extends existing ontological models and traditional frame-based formalisms. This work was motivated by the representational challenges posed by the domains of experimental sciences (biology, chemistry, physics) and the task of intelligent text retrieval. A detailed ontology for the field of experimental molecular biology is presented, which is used to illustrate the need for and application of the features of the framework. An extended frame-based formalism is defined to support these features. The ability of the framework to support intelligent retrieval from a knowledge base of molecular-biology research papers is demonstrated by providing answers to queries that could not be fully answered using previous approaches. The extensions to ontological framework include : category conversions, processes that change the category or identity of their participants; object histories to track substances through a series of experimental processes, including category conversions; object complexes, temporary configurations of objects with properties of their own; and process complexes, groups or sequences of interrelated actions that comprise an experimental technique or procedure. Features of the frame-based formalism include: slot groups for identifying sets of relations that license common inferences; and open-filler classes that combine knowledge of likely slot values with the ability to handle unexpected values. Evaluation techniques that are used to assess the adequacy of the ontology are presented: the ontologys conceptual coverage of the domain, its potential usefulness in improving the quality of query answering, and its formal consistency and reusability by the knowledge-sharing community are evaluated.

Interaction of Knowledge Sources in a Portable Natural Language Interface

This paper describes a general approach to the design of natural language interfaces that has evolved during the development of DATALOG, an English database query system based on Cascaded ATN grammar. By providing separate representation schemes for linguistic knowledge, general world knowledge, and application domain knowledge, DATALOG achieves a high degree of portability and extendability.

Improving dictionary-based disambiguation text entry method accuracy

Text entry on mobile devices is problematic because of ever-decreasing device sizes. Dictionary-based keypad text entry methods are relatively effective, but still run into problems of word ambiguity, especially when used with small numbers of keys. Common text entry disambiguation methods only use word frequency information to resolve conflicts. This paper proposes a new method that also looks at semantic information (distances between word meanings). Simulations show encouraging results, suggesting potential practical applications of this method to mobile devices.

SEMANTICS OF TEMPORAL QUERIES AND TEMPORAL DATA

This paper analyzes the requirements for adding a temporal reasoning component to a natural language database query system, and proposes a computational model that satisfies those requirements. A preliminary implementation in Prolog is used to generate examples of the models capabilities.