Week of 04/18/2010 - 02:00 to 04/25/2010 - 01:59

HD Maps: And Where Are The F*&*() Topics?

(continued from Part III)

Now that I know where the documents are located in the landscape, I have experimented with ways to estimate where the topic map topics are supposed to be. My hypothesis is that if I can determine the distance of each document to every topic, I can triangulate the topics.

Topic Positions

Below (larger version in the attachments) is a new rendering of the MapReduce theme:


It shows the themes derived from the semantic corpus (documents + semantic network). Compare this with the positions of topics:

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DeepZoom: new Graphics::DZI release

There are two major additions:

  • The first allows you to use a whole image stack as canvas for your image pyramid.
  • The other provides you with a more convenient and shorter way where things are supposed to be stored.

Image Stacks

The amazing Image::Magick package can cope with images which are linked together:

use Image::Magick;
my $image = Image::Magick->new;

If you resiz

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Use Case: Semantic Document Recovery

(continued from HD Semantic Maps)

Like most of you, I collect bookmarks. But unlike most of you, I store them into a semantic network, a topic map to be precise.

One problem I certainly share with you, is that all these laboriously collected links are prone to break. To recover them sometimes needs considerable effort and - according to another Murphy Law (are there actually any other laws?) - always hits you at the most inappropriate time.

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