Showing papers on "Knowledge sharing published in 1991"

Enabling technology for knowledge sharing

Abstract: Building new knowledge-based systems today usually entails constructing new knowledge bases from scratch. It could instead be done by assembling reusable components. System developers would then only need to worry about creating the specialized knowledge and reasoners new to the specific task of their system. This new system would interoperate with existing systems, using them to perform some of its reasoning. In this way, declarative knowledge, problem- solving techniques, and reasoning services could all be shared among systems. This approach would facilitate building bigger and better systems cheaply. The infrastructure to support such sharing and reuse would lead to greater ubiquity of these systems, potentially transforming the knowledge industry. This article presents a vision of the future in which knowledge-based system development and operation is facilitated by infrastructure and technology for knowledge sharing. It describes an initiative currently under way to develop these ideas and suggests steps that must be taken in the future to try to realize this vision.

An Overview of KQML: A Knowledge Query and Manipulation Language

Abstract: We describe a language and protocol intended to support interoperability among intelligent agents in a distributed application. Examples of applications envisioned include intelligent multi-agent design systems as well as intelligent planning, scheduling and replanning agents supporting distributed transportation planning and scheduling applications. The language, KQML for Knowledge Query and Manipulation Language, is part of a larger DARPA-sponsored Knowledge Sharing e ort focused on developing techniques and tools to promote the sharing on knowledge in intelligent systems. e will de ne the concepts which underly KQML and attempt to specify its scope and provide a model for how it will be used. Please send comments to Tim Finin, Computer Science, University of Maryland, Baltimore MD 21228; nin@cs.umbc.edu; 410-455-3522 or to Don Mckay, Paramax Systems Corporation, PO Box 517, Paoli PA 19301; mckay@prc.unisys.com; 215-648-2256. This work is partly supported by DARPA and Rome Laboratory under USAF contract F30602-91-C-0040. **** DRAFT **** 1 **** DRAFT ****

Why are governmental R&D and private R&D complements?

Abstract: It is well known that government R&D and private R&D have a complementary relationship. However, no previous study has provided an explanation for why that complementary relationship exists. This paper argues that infratechnology is the critical link between governmental and private R&D and that the observed complementarity is the result of technical complementarity at the production level between funding, infratechnology, and knowledge sharing. A theoritical framework based on this argument is developed and examined empirically for supporting evidence. Evidence of technical complementary is found as well as evidence that governmental R&D stimulates the sharing of knowledge.

Knowledge representation in pharmacology. A possible application area for the Arden Syntax

Abstract: In 1990 the Arden Syntax was proposed as a first version of a standardized syntax for the representation of medical knowledge. For the evaluation of the practicability of this first release we have analyzed the medical and pharmacological knowledge applied in the process of drug prescription. The separation of declarative (e.g. in a semantic network) and procedural knowledge is a basic issue of our research. We therefore propose to further extend the Arden syntax with declarative knowledge representation facilities. One way to do this may be the incorporation of a standardized medical data dictionary (e.g. the UMLS Metathesaurus) which promotes the representation of medical terms in a semantic network. Furthermore the problem of 'institution-specific knowledge', which is especially important for the issue of knowledge sharing between different institutions, is analyzed based on examples of knowledge modules for monitoring drug allergies and drug-drug-interactions.

A taxonomy of individual learning benefits from external knowledge‐sharing meetings

Abstract: Several knowledge-sharing and problem-solving roundtable groups, composed primarily of marketing executives from Fortune 500 companies, were studied through participant observation, analysis of audiotapes of the meetings, and unstructured follow-up interviews. Ten categories of potential learning benefit were identified through theme analysis: (1) new knowledge, (2) conditions for discovery and insight, (3) colleague resource networks, (4) awareness of information resources, (5) broad knowledge base, (6) new cognitive skills, (7) definition and clarification of terminology, (8) confirmation of thought, (9) awareness of knowledge deficits, and (10) self-comparison of professional competence. These ten benefits were then classified into three major domains (information access, cognitive development outcomes, and self-evaluation) and analyzed for taxonomy development.

An integrated system for knowledge sharing among heterogeneous knowledge derivation systems

Abstract: Solving problems in a complex application domain often requires a seamles integration of some existing knowledge derivation systems which have been independently developed for solving subproblems using different inferencing schemes. This paper presents the design and implementation of an Integrated Knowledge Derivation System (IKDS) which allows the user to query against a global database containing data derivable by the rules and constraints of a number of cooperative heterogeneous systems. The global knowledge representation scheme, the global knowledge manipulation language and the global knowledge processing mechanism of IKDS are described in detail. For global knowledge representation, the dynamic aspects of knowledge such as derivational relationships and restrictive dependencies among data items are modeled by a Function Graph to uniformly represent the capabilities (or knowledge) of the rule-based systems, while the usual static aspects such as data items and their structural interrelationships are modeled by an object-oriented model. For knowledge manipulation, three types of high-level, exploratory queries are introduced to allow the user to query the global knowledge base. For deriving the best global answers for queries, the global knowledge processing mechanism allows the rules and constraints in different component systems to be indiscriminately exploited despite the incompatibilities in their inferencing mechanisms and interpretation schemes. Several key algorithms required for the knowledge processing mechanism are described in this paper. The main advantage of this integration approach is that rules and constraints can in effect be shared among heterogeneous rule-based systems so that they can freely exchange their data and operate as parts of a single system. IKDS achieves the integration at the rule level instead of at the system level. It has been implemented in C running in a network of heterogenous component systems which contain three independently developed expert systems with different rule formats and inferencing mechanisms.

An integrated approach to knowledge sharing among heterogeneous rule-based systems

Abstract: To specify knowledge in the forms of rules and constraints has been widely accepted as a powerful methodology to extend the traditional databases. Rules and constraints can preexist, just as data can exist prior to the introduction of any integrated system over them. An approach to the integration of heterogeneous rule-based systems has been developed and the results are presented in this dissertation. Our approach achieves the integration of heterogeneous knowledge derivation systems not at the system level, but at the rule level. That is, this approach allows the best of relevant rules and constraints to be selected in a global perspective and be executed regardless of which component systems these selected rules and constraints belong to. This integration approach consists of three parts: a global knowledge representation scheme, a global knowledge manipulation language, and a global knowledge processing mechanism. In the global knowledge representation, the dynamic aspects of knowledge such as derivational relationships and restrictive dependencies among data items are graphically modeled by a Functional Graph to uniformly represent the capabilities (or knowledge) of the rule-based systems, while the usual static aspects such as data items and their structural interrelationships are modeled by an objected-oriented data model. For knowledge manipulation, high-level operations different from the usual data retrieval and storage operations are developed. For deriving the best global answers for high-level queries, the global knowledge processing mechanism allows the rules and constraints in different component systems to be indiscriminately exploited despite the incompatibilities in their inferencing mechanisms and interpretation schemes. One advantage of this approach is that rules and constraints can in effect be shared among heterogeneous rule-based systems. As a result, this integration approach allows the independent component systems to exchange their knowledge as well as data as if they were parts of a single system. The integration approach has been verified by an implementation.

Emerging applications of knowledge sharing systems

Abstract: Knowledge sharing systems represent a novel category of knowledge-based systems intended to overcome expert systems limitations in their application to ill-structured domains. Knowledge sharing systems provide an effective approach to knowledge sharing and knowledge transfer among people, particularly in multidisciplinary or decentralized-expertise fields. The author proposes knowledge sharing systems applications in such emerging areas as concurrent engineering, intelligent-organizational decision support systems, knowledge-based technology transfer, and new quality control. >

Descriptive results of an AIDS education program for adolescents

Abstract: This study describes the results of an acquired immunodeficiency syndrome (AIDS) education program for adolescents. Questions addressed were: "Is there a relationship between predisposing factors of age, gender, education, ethnicity, and knowledge and enabling factors of self-efficacy and knowledge sharing?" and "Is there a difference in participants' predisposing factor of knowledge and enabling factors of self-efficacy and knowledge sharing before and after the AIDS education program?" A portion of the PRECEDE model was used to evaluate relationships among factors thought to be influenced by health education. No significant relationship was found between the predisposing factors of age, gender, ethnicity, and education and the enabling factors of self-efficacy and knowledge sharing. At outcome there was a significant negative correlation between knowledge and self-efficacy, but no significant relationship between knowledge and knowledge sharing. There was no statistical significant difference from baseline to outcome measurement for the variables of knowledge, self-efficacy, and knowledge sharing.

An expert system for predicting flutter in turbomachines

Abstract: A framework of expert systems for predicting turbomachine blade flutter is proposed, which can be charactcrizcd by knowledge sharing through humancomputcr cooperation. The knowledge structure of fluttcr prediction is analyzcd by using ontological analysis method from the knowledge engincering point of view, based on which thc structure of thc knowlcdge basc and the infcrcnce cnginc of the systcm arc discussed. Some examplcs of production rules, inference mechanisms and knowledge association procedures for predicting fluttcr arc dcmonstratcd. The expected bcncfits of the systcm includc 1) helping cnginc dcsigncrs prcdict and avoid fluttcr, 2) helping fluttcr researchers improve their understanding of flutter phcnomcna by using and sharing knowlcdgc more cffectively.