Algorithm for discarding geographically disgregate points The context:
I'm working on geocoded documents. This is, documents have  latitude and longitude attributes, as well as some other geo attributes such as an address. Right now, I'm performing text search operations on the indexed docs and showing their geolocation on a map. 
The problem:
Most of search criterias include a location expressed by a name. But this name may appear in the document in fields other than those that express location. This usally gives irrelevan results on the map. 
In other cases, a doc within a resultset may be wrongly geocoded.
I both cases, the consequence is that the map appears with some relevant results geographically grouped and a few irrelevant results scattered far away.
The required solution:
I'm stuck trying to find an algorithm that processes the latitude/longitude of each doc in the results to determine which points are grouped and discard those that are not grouped.
Any ideas? Thanks in advance!

You can look, for each point, at the maximum distance among the $k$ nearest neighbors, and throw the point away if the maximum is too big (perhaps, relative to some average score on the specific map). You can determine $k$ by hand.
By the way, these points are known as outliers.
