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Mining Distance-Based Outliers from Categorical Data

Mining Distance-Based Outliers from Categorical Data,10.1109/ICDMW.2007.64,Shuxin Li,Robert Lee,Sheau-dong Lang

Mining Distance-Based Outliers from Categorical Data   (Citations: 2)
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    • ...Category Synonymous usage Paper Algorithm [27]; [28]; [29] Approach [30]; [31] Architectural style [32] Architecture Tool architecture [33]; [34]; [35] Concept Modeling concept [36]; [33]; [37] Construct [36] Design artifact [38] Design guidelines [39] Design implications [40] Evaluation [41]; [42]; [43]; [40]; [44]; [45]; [46] Framework Process Framework [41]; [47]; [48]; [39]; [49]; [50] Grammar Modeling grammar [51]; [37] Graphical ...
    • ...Algorithm Description Executable description of system behavior [27]; [28]; [29]; [67]; [61]; [32]...

    Philipp Offermannet al. Artifact Types in Information Systems Design Science - A Literature Re...

    • ...Presently, there are mainly two kinds of main-stream algorithms [6][5][4] designed for outlier detection from categorical data sets, such as proximity-based methods and rule-based methods...
    • ...CNB [6] is a distance-based outlier detection method, which employs a common-neighbor-based distance function between a pair of data objects for categorical data and calculates k nearest neighbors with similarity threshold θ of each object...
    • ...We choose the objects in small classes of a data set as the most likely anomalies using the same strategy as [5][6]...
    • ...From theory analysis, we know the time complexities of LOF [14] and CNB [6] increase quadratically with the number of objects...

    Shu Wuet al. Parameter-Free Anomaly Detection for Categorical Data

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