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Intelligent Systems in Accounting, Finance & Management

Steve G. Sutton et al.

Intelligent Systems in Accounting, Finance and Management: An International Journal2006https://doi.org/10.1002/(issn)1099-1174paratext
ABDC B
Weight
0.35

Abstract

Problem solving in the tax domain requires two kinds of knowledge: of the law itself and of how the law has been applied in the past. The need for the second factor arises as a result of the ambiguity of natural language. The problem solver requires information on how the courts have adjudicated specific cases in the past. This information would then provide the basis for reasoning about the current case. In this paper we address the issue of developing a system which will retrieve relevant historical cases. The cases are stored using a frame representation scheme and the users can retrieve cases by specifying either attributes alone or attributes and values associated with them. Currently the system has been implemented in Pascal on a Cray. The case base contains 250 cases relating to Section 183 of the tax code.

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https://doi.org/https://doi.org/10.1002/(issn)1099-1174

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@article{steve2006,
  title        = {{Intelligent Systems in Accounting, Finance & Management}},
  author       = {Steve G. Sutton et al.},
  journal      = {Intelligent Systems in Accounting, Finance and Management: An International Journal},
  year         = {2006},
  doi          = {https://doi.org/https://doi.org/10.1002/(issn)1099-1174},
}

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Intelligent Systems in Accounting, Finance & Management

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Evidence weight

0.35

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.20 × 0.15 = 0.03
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.