| Driven IFS is a potentially interesting tool for analyzing patterns in
data, but we need to be careful with how the data are binned. |
| A text is a string,
but in an alphabet of more than four symbols. How can we convert this into a string
in an alphabet of four symbols? |
| One possibility is to treat words as the fundamental units of
the text, and assign bins by parts of speech.
This has an obvious problem: distinguishing how much of the driven IFS structure is due to
the author's style, and how much to grammatical constraints. |
| Another choice is to treat letters as the
fundamental units and
assign bins by ignoring some letters, or grouping the letters together. Of course,
any choices must be justified in a way reflecting properties of the text. This is not
an easy problem. |
| Finding a meaningful translation of text into a symbol string suitable for driving
an IFS is an intricate problem. But this is a very good feature of the driven IFS
approach: it encourages experimentation with different methods, thought about
open-ended problems, questions for which there are no right answers. In
addition, it can lead to good mathematical
questions about the driven IFS itself. |
|
| Here are four examples of recent student projects. |
| Investigating the authorship of chapters of
Genesis using gemantria to convert text to numbers. |
| Comparing the sound patterns of
sonnets using the soundex algorithm to convert
text to numbers. |
| Olaf Schneider's analysis of shot duration and distance in film. |
| Phonological analysis of English texts. |
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