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posted by Fnord666 on Tuesday December 13 2016, @07:46AM   Printer-friendly
from the come-on-feel-the-noize dept.

This insight into the information which can be gleaned from data is cool and worrisome by equal measures.

Early in his talk, computer scientist John Hopcroft noted a funny fact about clustering algorithms: they work better on synthetic data than real data. But this is more than an odd tidbit about software.

[...] When we invent our own synthetic data, we try to mimic real data by mixing true information with random distraction–combining "signal" with "noise." But in real data, the divide isn't so clear. What often looks like noise turns out to be the deep structure we haven't grasped yet.

Hopcroft's insight: data doesn't just have one structure. It has many. If I scanned notebooks from a hundred people, and made a database of all the individual letters, I could sort them lots of ways. Alphabetically. Capital/lowercase. Size. Darkness. Handwriting. Each of these is a different layer of structure.

And to understand data–and the world–you've got to reckon with all those layers.

The part of the video which discusses the above starts around 5:45.


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  • (Score: 0) by Anonymous Coward on Tuesday December 13 2016, @08:39AM

    by Anonymous Coward on Tuesday December 13 2016, @08:39AM (#440723)

    For example, Hopcroft and his colleagues ran their algorithm on Facebook data from Rice University. They had sparse information: no names, no profiles, just who was friends with whom—a skeleton network of connections. Based on this, their algorithm quickly sorted the students into nine clusters.

    I can't help but wonder if there was a facebook profile for each dorm, that you would only friend to get news if you were part of that dorm... and similar for the year level.

    I'd also expect that they looked for "communities" within each cluster. In the case of the dorms you would expect to see 1-4 communities found proportional to the distribution of student years for each of the 9. There is something wrong about treating these as parallel rather than hierarchical clusters I think, maybe not though since I can't put my finger on it at the moment... but I feel like it is throwing out information.

  • (Score: -1, Offtopic) by Anonymous Coward on Tuesday December 13 2016, @12:31PM

    by Anonymous Coward on Tuesday December 13 2016, @12:31PM (#440757)

    Maybe he was trying to be politically correct?