摘要:

AbstractCROSBY III automatically constructs explanations for financial results. The key elements of the program are (1) a body of raw financial data to be explained, (2) an extensible knowledge base of financial relations expressed as algebraic constraints, (3) a selection of possible explanatory variables and information about the relative likelihoods of individual hypotheses, (4) an algorithm for generating consistent, adequate, plausible and parsimonious interpretations of the data, (5) a facility for explaining how a particular interpretation supports the data and (6) a facility for explaining why one interpretation is preferred over another. This paper focuses on facilites (5) and (6). CROSBY III is an implemented but undeployed prototype that has been tested on historical data and financial models of a small high‐technology company along with its closest competitors, on more than ten divisions of a large company and on a collection of large banks.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1994.tb00051.x

出版商:Wiley    

年代:2014

数据来源: WILEY

摘要:

AbstractExpert system explanations sometimes fail to satisfy their users. The standard assumption is that these failures arise because the user did not completely understand the system's explanation. However, users may also be left unsatisfied because they are unconvinced by the explanation provided. Advice‐giving systems should therefore eventually be extended to recognize when and why an explanation has failed to convince the user and to elaborate or revise explanations to make them more convincing. This paper provides an initial model of this process for systems that give advice about choosing between multiple alternatives for accomplishing a particular task. In particular, we discuss the model underlying a prototype system to advise novice computer users about how best to accomplish tasks on the UNIX operating system.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1994.tb00052.x

出版商:Wiley    

年代:2014

数据来源: WILEY

摘要:

AbstractAmong the various means that have been advanced for handling uncertainty in expert systems, certainty factor (CF) approaches have been widely adopted in both individual expert system applications and shells for building such systems. Nevertheless, CF approaches have been challenged on analytical grounds. This paper examines the descriptive efficacy of CF approaches from an empirical standpoint. Specifically, it compares conventional CF methods for certainty‐combining situations in a rule's premise with experimentally observed behaviors. The experimental data are subjected to ‘hit’ analyses that present the percentages of experts adhering to conventional algebraic means for combining CFs. The findings indicate that anywhere from about one‐fourth up to nine‐tenths of subjects combine certainties in a way consistent with CF algebras conventionally mapped into various certainty‐combining situations. Put another way, conventional CF algebra mappings are inadequate for describing anywhere from 10% to 75% of human behaviors across the situations studied here. This empirical evidence suggests that knowledge engineers should be cautious about adopting conventional CF algebras, particularly under certain circumstances identified in this study. It also suggests the prudence of considering uncertainty treatments other than conventional certainty factor algebras.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1994.tb00053.x

出版商:Wiley    

年代:2014

数据来源: WILEY

摘要:

AbstractThis paper describes SCAN, a case‐based reasoning model for generating information system control recommendations. The purpose of the paper is to explain how a case‐based reasoner may be used to support inexperienced information system auditors in evaluating controls and proposing audit recommendations. As a case‐based reasoner, SCAN functions by reasoning by analogy to similar past cases. SCAN models audit experience as traces of past cases which are stored in a case knowledge base. In addition to a database of past audit cases, SCAN consists of indices for storing and retrieving cases, a similarity metric for measuring case similarity, and rules for using similar cases to generate control recommendations. SCAN uses past cases to remind the user of previous control failures, to set expectations about case features and controls, to use as a pattern against which to compare a client's controls and to help justify or explain its recommendations. SCAN's recommendations were judged to be more like those of an experienced auditor than either a student or a textbook model.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1994.tb00054.x

出版商:Wiley    

年代:2014

数据来源: WILEY

摘要:

AbstractPLANET is an expert system for audit risk assessment and audit test selection. At present it is undergoing worldwide field testing by Price Waterhouse audit teams. As a case study, PLANET illustrates a complex interplay of audit methodology issues and expert systems development techniques, and reinforces the validity of many of the widely reported lessons learned about successful expert systems development during the 1980s. However, the experience also challenges elements of this received wisdom while exposing special issues arising in the development of expert systems in the field of auditing.

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1994.tb00055.x

出版商:Wiley    

年代:2014

数据来源: WILEY

ISSN:1055-615X    

DOI:10.1002/j.1099-1174.1994.tb00056.x

出版商:Wiley    

年代:2014

数据来源: WILEY