The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.
Propositionalization Approaches to Relational Data Mining
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Cites
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A TUTORIAL ON SUPPORT VECTOR MACHINES FOR PATTERN RECOGNITION, DATA MINING AND KNOWLEDGE DISCOVERY
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Solving the multiple instance problem with axis-parallel rectangles
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Fast discovery of association rules
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Estimation of Dependences Based on Empirical Data
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Cited by
Collective Classification in Network Data
Sen, P., Namata, G., Bilgic, M., Getoor, L., Gallagher, B., & Eliassi‐Rad, T. (2008) · AI Magazine · doi:10.1609/aimag.v29i3.2157 · Cited by 3,293
Fraud detection system: A survey
Abdallah, A., Maarof, M. A., & Zainal, A. (2016) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2016.04.007 · Cited by 708
Patki, N., Wedge, R., & Veeramachaneni, K. (2016) · 2016 IEEE International Conference on Data Science and Advanced Analytics (DSAA) · doi:10.1109/dsaa.2016.49 · Cited by 616
Classification in Networked Data: A Toolkit and a Univariate Case Study
(2007) · Journal of Machine Learning Research · doi:10.5555/1248659.1248693 · Cited by 452
A review of some techniques for inclusion of domain-knowledge into deep neural networks
Dash, T., Chitlangia, S., Ahuja, A., & Srinivasan, A. (2022) · Scientific Reports · doi:10.1038/s41598-021-04590-0 · Cited by 196
Metadata
- Authors
- Kramer, S., Lavrač, N., & Flach, P.
- Venue
- Relational Data Mining
- Publisher
- Springer Berlin Heidelberg
- Published
- 2001
- Pages
- 262-291
- OpenAlex
- W1545331097
- Cited by
- 271
- References
- 54
- FWCI
- 49.77
- Type
- book chapter
- Language
- en
- Open access
- closed
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- Kramer, S., Lavrač, N., & Flach, P. (2001). Propositionalization Approaches to Relational Data Mining. Relational Data Mining. https://doi.org/10.1007/978-3-662-04599-2_11
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
