Abstract. The mining of outliers (or anomaly detection) in large databases continues to remain an active area of research with many potential applications.
Dec 18, 2013 · In this paper we propose a unique approach to mine for sequential outliers using Probabilistic Suffix Trees (PST). The key insight that ...
A unique approach to mine for sequential outliers using Probabilistic Suffix Trees (PST), which shows that on a real data set consisting of protein ...
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The mining of outliers (or anomaly detection) in large databases continues to remain an active area of research with many potential applications.
Jan 26, 2023 · It is used in sequence mining from large databases. Almost all sequence mining algorithms are basically based on a prior algorithm. GSP uses ...
This paper deals with finding outliers (ex- ceptions) in large, multidimensional datasets. The identification of outliers can lead to the.
This paper deals with finding outliers (excep- tions) in large datasets. The identification of outliers can often lead to the discovery of truly.
Apr 17, 2024 · Outlier is a data object that deviates significantly from the rest of the data objects and behaves in a different manner.
We present a novel algorithm, ApproxMAP, to mine approximate sequential patterns, called consensus patterns, from large sequence databases in two steps. First, ...
database for mining sequential patterns which require a lot of memory [11]. To solve this problem, pattern-growth approach as an extension of FP-growth.