Work

FRaC: a feature-modeling approach for semi-supervised and unsupervised anomaly detection

Year: 2011

Type: article

Source: Data Mining and Knowledge Discovery

DOI: 10.1007/s10618-011-0234-x

Authors: Keith Noto, Carla Brodley, Donna Slonim

Institution: Tufts University

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, National Institutes of Health, Eunice Kennedy Shriver National Institute of Child Health and Human Development

Award: G958130886

OpenAlex ID: W2010921848

FWCI: 3.531

Cites: 24

Cited by: 79

Related to: 10