… the model proposed in this work uses a post-processing similarity score between input
and reconstructed signals. In terms of the AUC score, the model proposed in this work (Ours) …

… when similarities are “too high” or “too low.” In this paper, we focus on anomaly detection for
… We do this by computing one or more similarity scores between two consecutive web graphs…

… We therefore train a semantic similarity score, s(x, x′), to detect semantic differences
between nearby examples on the unit-hypersphere, which are determined by the readily trained …

… Other than these two issues, the supervised anomaly detection problem is similar to
building … Scoring-based anomaly detection techniques allow the analyst to use a domainspecific …

… This paper examines the use of distance and similarity measures as used in Network
Intrusion Detection (NID). There are a set of fundamental definitions of distance measures as …

… anomaly detection method called similarity-measured isolation forest (SM-iForest) is proposed
to detect … Thereafter, the feature matrix was reused to measure the anomaly score of each …

… related work in graph mining, anomaly detection, and the high-… of anomalies that these
algorithms detect, namely, anomalous … of the changes in similarity scores. Edges with the highest …

… To examine the hypothesis that detecting match adjacency is useful for this task, we modified
MC-P to bias the similarity score in favor of adjacent matches (as described below). This …

… was indicated, the anomaly score provided by this … anomaly score produced by EXPoSE.
To that end, the idea of Conformal Anomaly Detection is adopted to build an anomaly detector …

… enabling our approach is that the distribution of the normal examples’ anomaly scores in
both domains will be similar if they are derived using the same anomaly detection algorithm. …