@inproceedings{10.1007/978-3-031-24801-6_36,
  abstract = {Anomaly detection is an important task in many fields such as eHealth and online fraud. In this paper, we propose a new technique for anomaly detection based on a graph that connects transactions with the same attribute values and searches for dense clusters indicative of an anomalous pattern. The experimental evaluation shows that the graph-based approach outperforms two other approaches in the considered dataset. The extension of this approach to the eHealth domain is reserved as future work.},
  added-at = {2024-02-07T10:24:36.000+0100},
  address = {Cham},
  author = {Brauer, Steffen and Fisichella, Marco and Lax, Gianluca and Romeo, Carlo and Russo, Antonia},
  biburl = {https://www.bibsonomy.org/bibtex/260ff0faf9b119502b50060b8217dcd16/l3s},
  booktitle = {Applied Intelligence and Informatics},
  description = {A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values | SpringerLink},
  editor = {Mahmud, Mufti and Ieracitano, Cosimo and Kaiser, M. Shamim and Mammone, Nadia and Morabito, Francesco Carlo},
  interhash = {5062dfafa5d66ee6f1a88f5541b3693b},
  intrahash = {60ff0faf9b119502b50060b8217dcd16},
  isbn = {978-3-031-24801-6},
  keywords = {myown from:mfisichella},
  pages = {511--522},
  publisher = {Springer Nature Switzerland},
  timestamp = {2024-02-07T10:24:36.000+0100},
  title = {A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values},
  year = 2022
}

@inproceedings{10.1007/978-3-031-24801-6_36,
  abstract = {Anomaly detection is an important task in many fields such as eHealth and online fraud. In this paper, we propose a new technique for anomaly detection based on a graph that connects transactions with the same attribute values and searches for dense clusters indicative of an anomalous pattern. The experimental evaluation shows that the graph-based approach outperforms two other approaches in the considered dataset. The extension of this approach to the eHealth domain is reserved as future work.},
  added-at = {2023-03-19T17:41:21.000+0100},
  address = {Cham},
  author = {Brauer, Steffen and Fisichella, Marco and Lax, Gianluca and Romeo, Carlo and Russo, Antonia},
  biburl = {https://www.bibsonomy.org/bibtex/260ff0faf9b119502b50060b8217dcd16/mfisichella},
  booktitle = {Applied Intelligence and Informatics},
  description = {A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values | SpringerLink},
  editor = {Mahmud, Mufti and Ieracitano, Cosimo and Kaiser, M. Shamim and Mammone, Nadia and Morabito, Francesco Carlo},
  interhash = {5062dfafa5d66ee6f1a88f5541b3693b},
  intrahash = {60ff0faf9b119502b50060b8217dcd16},
  isbn = {978-3-031-24801-6},
  keywords = {myown},
  pages = {511--522},
  publisher = {Springer Nature Switzerland},
  timestamp = {2024-02-07T10:24:36.000+0100},
  title = {A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values},
  year = 2022
}

@inproceedings{conf/aii2/BrauerFLRR22,
  added-at = {2023-02-14T00:00:00.000+0100},
  author = {Brauer, Steffen and Fisichella, Marco and Lax, Gianluca and Romeo, Carlo and Russo, Antonia},
  biburl = {https://www.bibsonomy.org/bibtex/296d0cbd662c79b5d86133467826cfdaa/dblp},
  booktitle = {AII},
  ee = {https://doi.org/10.1007/978-3-031-24801-6_36},
  interhash = {5062dfafa5d66ee6f1a88f5541b3693b},
  intrahash = {96d0cbd662c79b5d86133467826cfdaa},
  keywords = {dblp},
  pages = {511-522},
  timestamp = {2024-04-09T07:59:42.000+0200},
  title = {A Graph-Based Approach to Detect Anomalies Based on Shared Attribute Values.},
  url = {http://dblp.uni-trier.de/db/conf/aii2/aii2022.html#BrauerFLRR22},
  year = 2022
}