B. R. Gaines and J. H. Boose. Knowledge Acquisition for Knowledge-Based Systems. London: Academic, 1988.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....for mining in object oriented databases and the applications of discovered knowledge are discussed, and the study is summarized in Section 7. 2 Primitives for knowledge discovery in object oriented databases There are different philosophical considerations on knowledge discovery in databases [21, 20, 58], which may lead to different methodologies in the development of knowledge discovery techniques. To simplify our discussion, an evolutionary approach is adopted, that is, starting from simple assumptions and relaxing them step by step to handle more complicated cases. Assumption 2.1 An ....

B. R. Gaines and J. H. Boose. Knowledge Acquisition for Knowledge-Based Systems. London: Academic, 1988.

.... as one of the most important research topics in 1990s by both machine learning and database researchers [17, 20] There are different philosophical considerations on knowledge discovery in databases (KDD) 5, 23] which may lead to different methodologies in the development of KDD techniques [5, 11, 6, 18, 1, 21, 22, 23]. In our previous studies [2, 7, 8] an attribute oriented induction method has been developed for knowledge discovery in relational databases. The method integrates a machine learning paradigm, especially learningfrom examples techniques, with database operations and efficiently extracts ....

B. R. GMnes and J. H. Boose. Knowledge Acquisition for Knowledge-Based Systems. London: Academic, 1988.

....and attributes applied in the problem solving process were not described during any previous interviews and, moreover, many of these objects did not seem to have any verbal description that people other than the expert could understand or use unambiguously. The same results were also found by Gaines (1988) and the Shadbolt and Burton (1990) when evaluating knowledge acquisition tools for classification domains. In the Shadbolt and Burton s experiment, protocol analysis applied to an igneous rock identification task performed very poorly, mainly because the elicitation sessions did not reveal ....

.... To date, knowledge engineering fails to provide enough instruments to elicit and understand the inference process that puts expertise to work (Reiman and Biolsi, 1991) This observation results throughout the literature, where many projects have been undertaken to explain knowledge structures (Gaines and Boose, 1988; McGraw and Westphal 1990, Hoffman 1994) 8 with no more than mentioning the possible underlying thinking procedure that uses them to derive new information. Furthermore, this limitation also touches the software tools available for building expert systems, which provide rich and complex formats ....

Gaines, B.R. and Boose, J.H. , eds., 1988, Knowledge acquisition for knowledge-based systems: Knowledge-based Systems, v. 1., London, United Kingdom, Academic Press.

....framework is implemented as a prototype, is rigorously tested and evaluated, and conclusions are derived from the work. Page 2 1. Introduction The most commonly used knowledge acquisition approach is to employ a competent knowledge engineer as an intermediate between the expert and the system [1]. A query process is repeated until the amount, the form, and the quality of the knowledge acquired is satisfactory for the current problem. This is a tedious and time consuming process, which has major drawbacks that limit its effective use [2, 3] The use of automated knowledge acquisition ....

Boose, J. H., and Gaines, B. R. 1989. "Knowledge acquisition for Knowledge-based systems: Notes on the state-of-theart ", Machine Learning, 4, pp. 377-394.

....Jaime Carbonell, Jill Fain, Douglas Fisher, Herb Simon, and Manuela Veloso for their suggestions and support. for successful applications of planning systems (desJardins 1994; Chien 1996; Gil 1991) While considerable research has focused on knowledge acquisition tools for rule based systems (see (Boose and Gaines 1989) for a summary) and some on such tools for specialized planning systems (Chien 1994) these systems all require a considerable amount of direct interactions with domain experts. It is possible to automate the process of knowledge acquisition when a simulator is available, although there has been ....

J. H. Boose and B. R. Gaines. Knowledge acquisition for knowledge-based systems: Notes on the state-of-the-art. Machine Learning, 4:377--394, 1989.

....al. 1994] For example, significant effort has been devoted to writing and debugging planning operators for successful applications of planning systems [desJardins, 1994, Chien, 1994, Gil, 1991] While considerable research has focused on knowledge acquisition tools for rule based systems (see [Boose and Gaines, 1989] for a summary) and some on such tools for specialized planning systems [Chien, 1994] these systems all require a considerable amount of direct interactions with domain experts. It is possible to automate the process of knowledge acquisition when a simulator is available, although there has ....

J. H. Boose and B. R. Gaines. Knowledge acquisition for knowledge-based systems: Notes on the state-of-the-art. Machine Learning, 4:377-- 394, 1989.

....to him, a logical the3 At least, in the sense that the ontological commitment of a logical theory is intended as a set of individuals. Expressions like can exist in the mind are however extraneous to Quine. ory is ontologically committed to the entities it quantifies over. As discussed in [Guarino et al. 1994], such a notion however is too weak for our purposes, since we want not only an account of what exists, but also an account of the structure of what exists. This structure is implied in the language we use: this is the reason why, as noticed by the authors, the term ontology is often used as a ....

....description of a knowledge representation (p. 10) In my opinion, this definition introduces a source of confusion, due to the fact that the meta level view is considered by the authors as intrinsic to their notion ontology. Indeed, the ontologies they have used in their work on KAKTUS [Wielinga et al. 1994] and on the VT domain [Schreiber and Terpstra 1996] are meta level ontologies, since their domain is the meta level domain of representation primitives. However, the ontologies present in the core library built by Falasconi and Stefanelli [Falasconi and Stefanelli 1994] can hardly be seen as ....

[Article contains additional citation context not shown here]

In B. R. Gaines and J. H. Boose (eds.), Knowledge Acquisition for Knowledge Based Systems. Academic Press, London. Falasconi, S. and Stefanelli, M. 1994. A Library of Medical Ontologies. In Proceedings of ECAI94 Workshop on Comparison of Implemented Ontologies.

....for mining in object oriented databases and the applications of discovered knowledge are discussed, and the study is summarized in Section 7. 2 Primitives for knowledge discovery in object oriented databases There are different philosophical considerations on knowledge discovery in databases [21, 20, 58], which may lead to different methodologies in the development of knowledge discovery techniques. To simplify our discussion, an evolutionary approach is adopted, that is, starting from simple assumptions and relaxing them step by step to handle more complicated cases. Assumption 2.1 An ....

B. R. Gaines and J. H. Boose. Knowledge Acquisition for Knowledge-Based Systems. London: Academic, 1988.

.... as one of the most important research topics in 1990s by both machine learning and database researchers [17, 20] There are different philosophical considerations on knowledge discovery in databases (KDD) 5, 23] which may lead to different methodologies in the development of KDD techniques [5, 11, 6, 18, 1, 21, 22, 23]. In our previous studies [2, 7, 8] an attribute oriented induction method has been developed for knowledge discovery in relational databases. The method integrates a machine learning paradigm, especially learningfrom examples techniques, with database operations and efficiently extracts ....

B. R. Gaines and J. H. Boose. Knowledge Acquisition for Knowledge-Based Systems. London: Academic, 1988.

.... wide variety of such knowledge support systems developed by different research communities (Gaines, 1990b) for example: The knowledge acquisition community has generated requirements for systems to incorporate knowledge elicitation and analysis modules automating expertise transfer (Boose and Gaines, 1988; Gaines and Boose, 1988) The machine learning community has generated requirements for systems to incorporate inductive modeling modules automating empirical induction (Michalski, Carbonell and Mitchell, 1986) The case based reasoning community has generated requirements for systems to ....

.... of such knowledge support systems developed by different research communities (Gaines, 1990b) for example: The knowledge acquisition community has generated requirements for systems to incorporate knowledge elicitation and analysis modules automating expertise transfer (Boose and Gaines, 1988; Gaines and Boose, 1988). The machine learning community has generated requirements for systems to incorporate inductive modeling modules automating empirical induction (Michalski, Carbonell and Mitchell, 1986) The case based reasoning community has generated requirements for systems to incorporate comparison ....

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Gaines, B.R. and Boose, J.H. (1988). Knowledge Acquisition for Knowledge-based Systems. London, Academic Press.

.... may create as many problems as he or she solves (Gaines, 1987a) The computer itself is an excellent tool for helping the expert to structure the knowledge domain, and, in recent years research on knowledge acquisition has focused on the development of computer based acquisition tools (Boose Gaines, 1988; Gaines Boose, 1988; Boose, 1989) Many such tools are designed to be used directly by the expert with the minimum of intervention by the knowledge engineer, and emphasize facilities for visualizing the domain concepts. The objective of systems such as PLANET (Shaw Gaines, 1983, 1986, 1987a) ....

.... as many problems as he or she solves (Gaines, 1987a) The computer itself is an excellent tool for helping the expert to structure the knowledge domain, and, in recent years research on knowledge acquisition has focused on the development of computer based acquisition tools (Boose Gaines, 1988; Gaines Boose, 1988; Boose, 1989) Many such tools are designed to be used directly by the expert with the minimum of intervention by the knowledge engineer, and emphasize facilities for visualizing the domain concepts. The objective of systems such as PLANET (Shaw Gaines, 1983, 1986, 1987a) ETS (Boose, 1984, ....

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Gaines, B.R. & Boose, J.H., Eds. (1988). Knowledge Acquisition for Knowledge-Based Systems. London, Academic Press.

....guide knowledge acquisition theory and practice. INTRODUCTION There is currently a major paradigm split in knowledge acquisition research and practice between techniques for the transfer of existing knowledge from human experts and those for the creation of new expertise through machine learning (Gaines Boose 1988, Boose Gaines 1988) There is, however, a fundamental relation between the two paradigms in that existing expertise was at some time derived through empirical induction. There is also continuity between the two paradigms in that existing expertise may be partial, erroneous, and of various ....

....theory and practice. INTRODUCTION There is currently a major paradigm split in knowledge acquisition research and practice between techniques for the transfer of existing knowledge from human experts and those for the creation of new expertise through machine learning (Gaines Boose 1988, Boose Gaines 1988). There is, however, a fundamental relation between the two paradigms in that existing expertise was at some time derived through empirical induction. There is also continuity between the two paradigms in that existing expertise may be partial, erroneous, and of various forms, such that it cannot ....

Gaines, B.R. & Boose, J.H., Eds. (1988). Knowledge Acquisition for Knowledge-Based Systems.

.... may create as many problems as he or she solves (Gaines, 1987a) The computer itself is an excellent tool for helping the expert to structure the knowledge domain, and, in recent years research on knowledge acquisition has focused on the development of computer based acquisition tools (Boose Gaines, 1988; Gaines Boose, 1988; Boose, 1989) Many such tools are designed to be used directly by the expert with the minimum of intervention by the knowledge engineer, and emphasize facilities for visualizing the domain concepts. The objective of systems such as PLANET (Shaw Gaines, 1983, 1986, 1987a) ....

.... as many problems as he or she solves (Gaines, 1987a) The computer itself is an excellent tool for helping the expert to structure the knowledge domain, and, in recent years research on knowledge acquisition has focused on the development of computer based acquisition tools (Boose Gaines, 1988; Gaines Boose, 1988; Boose, 1989) Many such tools are designed to be used directly by the expert with the minimum of intervention by the knowledge engineer, and emphasize facilities for visualizing the domain concepts. The objective of systems such as PLANET (Shaw Gaines, 1983, 1986, 1987a) ETS (Boose, 1984, ....

[Article contains additional citation context not shown here]

Gaines, B.R. & Boose, J.H., Eds. (1988). Knowledge Acquisition for Knowledge-Based Systems. London, Academic Press.

....a role in that community. 3 Deriving Conceptual Systems Personal Construct Psychology (Kelly 1955, Shaw 1980) has been widely used as a basis for developing methods of knowledge acquisition from experts in a given domain (Shaw Gaines 1983, Boose 1984, Diederich, Ruhmann May 1987, Boose Gaines 1988, Gaines Boose 1988) Personal Construct Psychology is a psychology of the individual and many of its applications emphasize the idiosynchratic nature of conceptual systems (Mancuso Shaw 1988) However, it is also a psychology of the individual interacting with the world and embedded in ....

....that community. 3 Deriving Conceptual Systems Personal Construct Psychology (Kelly 1955, Shaw 1980) has been widely used as a basis for developing methods of knowledge acquisition from experts in a given domain (Shaw Gaines 1983, Boose 1984, Diederich, Ruhmann May 1987, Boose Gaines 1988, Gaines Boose 1988). Personal Construct Psychology is a psychology of the individual and many of its applications emphasize the idiosynchratic nature of conceptual systems (Mancuso Shaw 1988) However, it is also a psychology of the individual interacting with the world and embedded in society (Shaw 1985) It ....

Gaines, B.R. & Boose, J.H., Eds. (1988). Knowledge Acquisition for Knowledge-Based Systems. London, Academic Press.

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