The change of very first chart on page 91 was quite impressive and made me interest of the concept of maximizing data ink ratio. Today, unlike the period of 1980s, we have great quad processing computer that can do all the graphical designs using its own GPU which results in realistic visual on 3Ds. Even though I agree this theory of maximizing data ink ratio, I think some decoration is quite necessary to emphasize the data you are retrieving.

The Visual Display of Quantitative Information

[서평]「Algorithms on Strings, Trees, and Sequences」

Subspace clustering refers to the task of identifying clusters of similar objects or data records (vectors) where the similarity is defined with respect to a subset of the attributes (i.e., a subspace of the data space). The subspace is not necessarily (and actually is usually not) the same for different clusters within one clustering solution. In this article, the problems motivating subspace clustering are sketched, different definitions and usages of subspaces for clustering are described, and exemplary algorithmic solutions are discussed. Finally, we sketch current research directions. © 2012 Wiley Periodicals, Inc. © 2012 Wiley Periodicals, Inc.

Subspace clustering

Visual explanations: Images and quantities, evidence and narrative

Discovering recency, frequency, and monetary (RFM) sequential patterns from customers' purchasing data

Data Mining: Concepts and Techniques

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Data Mining: Concepts and Techniques