Found: 10
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On GNN explainability with activation rules.
- Published in:
- Data Mining & Knowledge Discovery, 2024, v. 38, n. 5, p. 3227, doi. 10.1007/s10618-022-00870-z
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- Article
Methods for explaining Top-N recommendations through subgroup discovery.
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- Data Mining & Knowledge Discovery, 2023, v. 37, n. 2, p. 833, doi. 10.1007/s10618-022-00897-2
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- Article
Sequential recommendation with metric models based on frequent sequences.
- Published in:
- Data Mining & Knowledge Discovery, 2021, v. 35, n. 3, p. 1087, doi. 10.1007/s10618-021-00744-w
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- Article
SIAS-miner: mining subjectively interesting attributed subgraphs.
- Published in:
- Data Mining & Knowledge Discovery, 2020, v. 34, n. 2, p. 355, doi. 10.1007/s10618-019-00664-w
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- Article
Identifying exceptional (dis)agreement between groups.
- Published in:
- Data Mining & Knowledge Discovery, 2020, v. 34, n. 2, p. 394, doi. 10.1007/s10618-019-00665-9
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- Publication type:
- Article
Rank correlated subgroup discovery.
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- Journal of Intelligent Information Systems, 2019, v. 53, n. 2, p. 305, doi. 10.1007/s10844-019-00555-y
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- Article
Chemical features mining provides new descriptive structure-odor relationships.
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- PLoS Computational Biology, 2019, v. 15, n. 4, p. 1, doi. 10.1371/journal.pcbi.1006945
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- Article
Mining exceptional closed patterns in attributed graphs.
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- Knowledge & Information Systems, 2018, v. 56, n. 1, p. 1, doi. 10.1007/s10115-017-1109-2
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- Publication type:
- Article
Exceptional contextual subgraph mining.
- Published in:
- Machine Learning, 2017, v. 106, n. 8, p. 1171, doi. 10.1007/s10994-016-5598-0
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- Publication type:
- Article
Finding maximal homogeneous clique sets.
- Published in:
- Knowledge & Information Systems, 2014, v. 39, n. 3, p. 579, doi. 10.1007/s10115-013-0625-y
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- Publication type:
- Article