A Web-based Interactive Data Visualization System for Outlier Subspace Analysis

Detecting outliers from high-dimensional data is a challenge task since outliers mainly reside in various lowdimensional subspaces of the data. To tackle this challenge, subspace analysis based outlier detection approach has been proposed recently. Detecting outlying subspaces in which a given data point is an outlier facilitates a better characterization process for detecting outliers for high-dimensional data stream, and make outlier mining for large high-dimensional data set to be more manageable. In this paper, to facilitate outlier subspaces analysis from human perception perspectives in supporting the development of efficient solutions for high-dimensional data, we propose a web-based interactive data visualization system, which can display various low-dimensional outlier subspaces to allow users to observe and analyze the distributions of outliers. The proposed visualization tool can help the developers of outlier detection applications to directly examine the distributions of outliers in various low-dimensional subspaces to validate their experiment results.