Hi Folks,
In working with eye-tracking data, a person's sequence of
areas-of-interest viewed (a "scan pattern") are often represented as
strings. E.g., my scan-pattern in the first 5 seconds of looking at a
webpage might be PPHM, with P = picture, H = headline, and M = side
menu.
For this reason, I am interested in clustering on string similarity,
to identify commonly-taken scan patterns in a dataset.
It looks like my best bet is to create a dissimilarity matrix (using
Levenshtein distance has the dissimilarity measure) and then use
-clustermat-.
My questions are:
-are there any packages out there that would make this easier?
-am I right that I will have to write a program to make the matrix?
I'm fine with writing it, I just want to confirm that I'm not missing
an easier way to do this.
Thanks in advance,
Dan
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