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Table 18: Knowledge acquisition results
2005
"... In PAGE 26: ... 5.3 Knowledge Acquisition Results The acquisition results are shown in Table18 . Due to space constraints, we only pro- vide a statistical summary of the results.... ..."
Cited by 3
Table 18: Knowledge acquisition results
2005
"... In PAGE 26: ... 5.3 Knowledge Acquisition Results The acquisition results are shown in Table18 . Due to space constraints, we only pro- vide a statistical summary of the results.... ..."
Cited by 3
Table 1: Comparison based on Knowledge Acquisition
"... In PAGE 26: ... The importance of the knowledge, in turn, raises the issue of the knowledge capture. Table1 shows a comparison of approaches studied in Section 2 in terms of the type of knowledge that they represent, the type of representation, and how this knowledge is captured. Rule-based systems rely heavily on reusing production rules with the excep- tion of the Programmer apos;s Apprentice.... ..."
Table 1: Comparison based on Knowledge Acquisition
1998
"... In PAGE 26: ... The importance of the knowledge, in turn, raises the issue of the knowledge capture. Table1 shows a comparison of approaches studied in Section 2 in terms of the type of knowledge that they represent, the type of representation, and how this knowledge is captured. Rule-based systems rely heavily on reusing production rules with the excep- tion of the Programmer apos;s Apprentice.... ..."
Table 2: Remoter modules OKM Phases OKM Modules Knowledge Acquisition Knowledge Acquisition, Knowledge Codify
Table 1: Activities modularization OKM Activities OKM Modules Knowledge Acquisition Knowledge Acquisition
Table 1. Automated/Semi-Automated Knowledge Acquisition for Diagnosis
"... In PAGE 11: ... It is viewed as one of the key approaches of reducing the knowledge acquisition bottleneck [Boose 91; Gaines and Shaw 91]. Table1 presents some recent noteworthy approaches for automated or semi-automated knowledge acquisition in diagnosis and their respective applications. In the first, the MOLTKE (MOdels, Learning and Temporal Knowledge in Expert sys- tems) testbed for diagnosis under development at the University of Kaiserslautern, Ger- many is described [Althoff et al.... ..."
Table 1. Automated/Semi-Automated Knowledge Acquisition for Diagnosis
in Summary
"... In PAGE 5: ... It is viewed as one of the key approaches of reducing the knowledge acquisition bottleneck [Boose 91; Gaines and Shaw 91]. Table1 presents some recent noteworthy approaches for automated or semi-automated knowledge acquisition in diagnosis and their respective applications. In the first, the MOLTKE (MOdels, Learning and Temporal Knowledge in Expert sys- tems) testbed for diagnosis under development at the University of Kaiserslautern, Ger- many is described [Althoff et al.... ..."
Table 1 . Knowledge acquisition systematization within the DA context
"... In PAGE 3: ...Table1... In PAGE 4: ...Table1 . Also, each acquisition technique is associated to a certain source of information with its corresponding representation (Table 2).... In PAGE 4: ...each acquisition technique is associated to a certain source of information with its corresponding representation (Table 2). While specifying and refining the systematic presented in Table1 , we conducted three case studies. These helped us to experience in practice the need for a knowledge acquisition systematic within the DA context.... In PAGE 4: ... These directives allow the adaptation of the systematic regarding the phases, activities and techniques that should be used in a certain project . The domain analyst identifies the context of his specific project by analyzing each of the directives provided, establishing which phases and activities, as well as the corresponding techniques, from the knowledge acquisition process described in Table1 , will his knowledge acquisition process be composed of. Technique Sources Representation Protocol Analysis Existing systems Facets Scenarios Existing systems Refinement Itemized Cards LEL 2 Written references Domain Vocabulary Itemized Text Brainstorming Specialists Users Numbered Text Structured interviews Specialists Users Structured Text Delphi technique Specialists Users Previous Formatted Report Self-explanation Domain analyst Inferences and deductions Previous representations Table 2 .... ..."
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