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Using Emergent Classification as a Starting (Not End) Point

By sleslie on October 21, 2004

http://www.adaptivepath.com/publications/essays/

From elearningpost comes mention of this useful article by Peter Merholz (some may remember him from ‘peterme‘ days, one of my earliest regular blog reads).

D’Arcy, King and I had been trading emails a few weeks back on the value of emergent classifications systems like those seen in Flickr for use in learning object repositories. Clearly, the idea is getting a bit of play, at least within the blogosphere.

What troubled me was that some of the current executions seemed a little bit like a baby/bathwater thing – yes, emergent classification systems are interesting and reflect actual users’ language usage, but they are also problematic – in being flattened, they do not have the depth (and the corresponding teaching ability) that hierarchical taxononmies can offer their users, and are also plagued with some of the problems Merholz points to. I mean, have you ever actually tried to find something you know should be there but didn’t know the classification for, (as opposed to just serendipidously browsing), in an flattened keyword system?

Instead, I think Merholz describes better than I did in my emails to D’Arcy and King what I think we should be looking towards – using ‘emergent’ temrs as the basis for creating connections between terms users actually use, as the basis for continual refinement of more complicated, less flattened, taxonomies.

How would this actually work – at the very least I think it could show up in things like ‘type ahead’ functionality that tries to complete the term you are entering based on previous ‘emergenet’ terms, or else asking the user to confirm whether they were using a term in one sense or another after they have submitted their choice. – SWL

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No responses to “Using Emergent Classification as a Starting (Not End) Point”

  1. Bruce Landon's Weblog for Students
    Bruce Landon's Weblog for Students
    October 21, 2004 at 10:34 am | Permalink

    Content mapping

    Using Emergent Classification as a Starting (Not End) Point .

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