Domain experts are frequently interested to analyze multiple related spatial datasets. This capability is important for change analysis and contrast mining. In this paper, a novel ...
Several techniques that compute the join between two spatial datasets have been proposed during the last decade. Among these methods, some consider existing indices for the joined...
Data mining is the process of extracting implicit, valuable, and interesting information from large sets of data. Visualization is the process of visually exploring data for patte...
Let a tuple of n objects obeying a query graph (QG) be called the n-tuple. The “Ddistance-value” of this n-tuple is the value of a linear function of distances of the n objects...
Antonio Corral, Yannis Manolopoulos, Yannis Theodo...
The immense explosion of geographically referenced data calls for efficient discovery of spatial knowledge. One critical requirement for spatial data mining is the capability to ...
Wei Ding 0003, Christoph F. Eick, Jing Wang 0007, ...
Outsourcing data to third party data providers is becoming a common practice for data owners to avoid the cost of managing and maintaining databases. Meanwhile, due to the populari...
Detecting changes in spatial datasets is important for many fields. In this paper, we introduce a methodology for change analysis in spatial datasets that combines contouring algor...
Christoph F. Eick, Chun-Sheng Chen, Michael D. Twa...
We consider the problem of joining massive datasets. We propose two techniques for minimizing disk I/O cost of join operations for both spatial and sequence data. Our techniques o...