I have an existing collection of lat/lons, each representing a place where a photo was taken. I want to computationally find the geographic clusters in this collection, i.e. the geographic areas with the densest concentrations of points. (So it sounds like Andrew's "location-closeness clustering" is what I'm thinking of.) Having found these most-photographed areas, I want to find the geographic name that best describes each area, such as a region, city, neighborhood or park name. So, I'm looking for two different things, a location-closeness clustering algorithm and a gazetteer lookup. Sorry to be confusing.
best,
--andrea
On 9/8/06, Andrew Turner <[EMAIL PROTECTED]> wrote:
Are you more interested in the "plot points" software, or the
"grouping algorithms"? What kind of clustering are you doing?
- Based on points users all tagged and therefore creating clusters of
"you like *this*, so you'll probably like *these*"?
- Location-closeness clustering
- Keyword terms based on generic names the points may have?
There are various algorithm/packages for any of the problems above.
And for creating points it would be easy to either use a current
service (of which there are many) and then apply your algorithms to
that (as Mike was suggesting), or roll your own using pieces of
existing mapping/archiving software packages available.
Andrew
On 9/8/06, Mike Liebhold <[EMAIL PROTECTED]> wrote:
>
> Hi andrea,
>
> you can record and map points easily with apps like platial.com by naming
> points with any plain language tag of your choice.
>
> cheers~
>
> -mike liebhold
>
> Andrea Moed wrote:
>
> For a webapp I'm hoping to build, I want to look at a collection of geo
> points, discover clusters of points and assign the clusters useful
> geographic names (where "useful" = good web search term). Does anyone know
> of freely available code for doing this?
> thanks much,
> --andrea
>
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--
Andrew Turner
[EMAIL PROTECTED] 42.4266N x 83.4931W
http://highearthorbit.com Northville, Michigan, USA
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