Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, volume 11, issue 1

A historical perspective of explainable Artificial Intelligence

Roberto Confalonieri ¹

Ludovik Coba ¹

Benedikt Wagner ²

Tarek R. Besold ³

Show full list: 4 authors

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Faculty of Computer Science Free University of Bozen‐Bolzano Bozen‐Bolzano Italy |

Research Centre for Machine Learning City University London UK |

Neurocat GmbH Berlin Germany |

Publication type: Journal Article

Publication date: 2020-10-19

Wiley

Journal: Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

scimago Q1

SJR: 2.147

CiteScore: 22.7

Impact factor: 6.4

ISSN: 19424787, 19424795

DOI: 10.1002/widm.1391

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Confalonieri R. et al. A historical perspective of explainable Artificial Intelligence // Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 2020. Vol. 11. No. 1.

GOST all authors (up to 50) Copy

Confalonieri R., Coba L., Wagner B., Besold T. R. A historical perspective of explainable Artificial Intelligence // Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 2020. Vol. 11. No. 1.

RIS |

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RIS Copy

TY - JOUR

DO - 10.1002/widm.1391

UR - https://doi.org/10.1002/widm.1391

TI - A historical perspective of explainable Artificial Intelligence

T2 - Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

AU - Confalonieri, Roberto

AU - Coba, Ludovik

AU - Wagner, Benedikt

AU - Besold, Tarek R.

PY - 2020

DA - 2020/10/19

PB - Wiley

IS - 1

VL - 11

SN - 1942-4787

SN - 1942-4795

ER -

BibTex

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BibTex (up to 50 authors) Copy

@article{2020_Confalonieri,

author = {Roberto Confalonieri and Ludovik Coba and Benedikt Wagner and Tarek R. Besold},

title = {A historical perspective of explainable Artificial Intelligence},

journal = {Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery},

year = {2020},

volume = {11},

publisher = {Wiley},

month = {oct},

url = {https://doi.org/10.1002/widm.1391},

number = {1},

doi = {10.1002/widm.1391}

}

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Publisher

Wiley

Journal

Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery

scimago Q1

SJR

2.147

CiteScore

22.7

Impact factor

6.4

ISSN

19424787 (Print)

19424795 (Electronic)