chapter  19
Concepts of Visual and Interactive Clustering
ByAlexander Hinneburg
Pages 22

Clustering algorithms group data objects together based on some notion of distance or similarity. This resembles visual tasks that are easy for humans: spotting a cluster of stars in the night sky or identifying a cluster of old houses within a modern city. The human visual system “has evolved to facilitate quick and considered detection of the visually like and unlike through a wide variety of cues – e.g. location and relative proximity, movement, shape, colour, texture, and matching against predetermined patterns. Consequently, visualization is a natural and powerful resource for cluster analysis; it is especially valuable in identifying unanticipated structure”[33].