While classic information retrieval methods return whole documents as a result of a query, many information demands would be better satisfied by fine-grain access inside the docu...
Many data sets exist that contain both geospatial and temporal elements. Within such data sets, it can be difficult to determine how the data have changed over spatial and tempor...
Orland Hoeber, Garnett Carl Wilson, Simon Harding,...
Knowledge discovery in databases has become an increasingly important research topic with the advent of wide area network computing. One of the crucial problems we study in this p...
We are working on a project aimed at building next generation analyst support tools that focus analysts’ attention on the most critical and novel information found within the da...
Clustering is one of the most important tasks for geographic knowledge discovery. However, existing clustering methods have two severe drawbacks for this purpose. First, spatial c...