Antonio Corral

Learn More
This paper addresses the problem of finding the K closest pairs between two spatial data sets, where each set is stored in a structure belonging in the R-tree family. Five different algorithms (four recursive and one iterative) are presented for solving this problem. The case of 1 closest pair is treated as a special case. An extensive study, based on(More)
This paper addresses the problem of finding the K closest pairs between two spatial datasets (the so called, K Closest Pairs Query, K-CPQ), where each dataset is stored in an R-tree. There are two different techniques for solving this kind of distance-based query. The first technique is the incremental approach, which returns the output elements one-by-one(More)
Let a tuple of n objects obeying a query graph (QG) be called the n-tuple. The “Ddistancevalue” of this n-tuple is the value of a linear function of distances of the n objects that make up this ntuple, according to the edges of the QG. This paper addresses the problem of finding the K n-tuples between n spatial datasets that have the smallest(More)
Efficient processing of distance-based queries (DBQs) is of great importance in spatial databases due to the wide area of applications that may address such queries. The most representative and known DBQs are the K Nearest Neighbors Query (KNNQ), q Distance Range Query (qDRQ), K Closest Pairs Query (KCPQ) and q Distance Join Query (qDJQ). In this paper, we(More)
In modern database applications the similarity or dissimilarity of complex objects is examined by performing distance-based queries (DBQs) on data of high dimensionality. The R-tree and its variations are commonly cited multidimensional access methods that can be used for answering such queries. Although, the related algorithms work well for low-dimensional(More)
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 that make up this n-tuple, according to the edges of the QG. This paper addresses the problem of finding the K n-tuples between n spatial datasets that have the smallest(More)