In this chapter, we discuss measures and benchmark datasets commonly used for Ad fraud detection. The measures include fraud detection accuracy, precision, recall, F-measure, and AUC scores which are commonly used to validate the performance of classifiers for classification. In addition, we also summarize several real-world datasets which are currently available for Ad detection and computational advertising research in general.
CITATION STYLE
Zhu, X., Tao, H., Wu, Z., Cao, J., Kalish, K., & Kayne, J. (2017). Ad fraud measure and benchmark. In SpringerBriefs in Computer Science (Vol. 0, pp. 39–44). Springer. https://doi.org/10.1007/978-3-319-56793-8_5
Mendeley helps you to discover research relevant for your work.