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Bookkeeping Graphs: Computational Theory and Applications

Pierre Jinghong Liang

Foundations and Trends in Accounting2023https://doi.org/10.1561/1400000070article
AJG 3ABDC A
Weight
0.43

What the paper says

This monograph first describes the graph or network rep­resentation of Double-Entry bookkeeping both in theory and in practice. The representation serves as the intellectual basis for a series of applied computational works on pattern recognition and anomaly detection in corporate journal- entry audit settings. The second part of the monograph reviews the computational theory of pattern recognition and anomaly detection built on the Minimum Description Length (MDL) principle. The main part of the monograph describes how the computational MDL theory is applied to recognize patterns and detect anomalous transactions in graphs representing the journal entries of a large set of transactions extracted from real-world corporate entities' bookkeeping data.

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https://doi.org/https://doi.org/10.1561/1400000070

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@article{pierre2023,
  title        = {{Bookkeeping Graphs: Computational Theory and Applications}},
  author       = {Pierre Jinghong Liang},
  journal      = {Foundations and Trends in Accounting},
  year         = {2023},
  doi          = {https://doi.org/https://doi.org/10.1561/1400000070},
}

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Bookkeeping Graphs: Computational Theory and Applications

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Evidence weight

0.43

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

F · citation impact0.22 × 0.4 = 0.09
M · momentum0.80 × 0.15 = 0.12
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.