Interactive local clustering operations for high dimensional data in parallel coordinates

Abstract

In this paper, we propose an approach of clustering data in parallel coordinates through interactive local operations. Different from many other methods in which clustering is globally applied to the whole dataset, our interactive scheme allows users to directly apply attractive and repulsive operators at regions of interests, taking advantages of an electricity interaction metaphor, for clutter reduction and cluster detection. Our design enables users to interact directly with the parallel coordinate plots and provides great flexibility in exploring and revealing underlying patterns. With instant feedback, our work allows users to dynamically adjust the clustering parameters to reach an optimum. We also supply the user with a graph indicating the logical relationship between clusters. Our experiments show that our scheme is more efficient than traditional methods in performing visual analysis tasks.

A Space-Filling Multidimensional Visualization (SFMDVis) for Exploratory Data Analysis

“…This observation is made in such a way that we note Guo [13] and Artero [4] have applied a clustering method to enhance the structure of the homogeneous data. Zhou et al [35] have contributed a visual clustering technique by allowing the user to specify transfer functions for controlling the density value of lines for alpha blending.…”

A novel virtual node approach for interactive visual analytics of big datasets in parallel coordinates

“…For example, in 2010 Guo et al [12] presented a sophisticated system of interactive parallel coordinates geometry with multitouch and dual view design. They proposed the concept of local operation by allowing the user to apply the attractive and repulsive operators at regions of interests directly in the parallel coordinate plots.…”

Circular Visualization Enhancement through Complementary Interaction

“…Peihong et.al. Proposed an interactive clustering using graph [15]. Interactive exploration of information using multiple view was proposed Sara Johansson in his work.…”