Topological operators: a relaxed query processing approach

Relaxation and approximation techniques have been proposed as approaches for improving the quality of query results, in terms of completeness and accuracy, in environments where the user may not be able to specify the query in a complete and exact way, since data are quite heterogeneous or she may not know all the characteristics of data at hand. This problem, mainly addressed for relational and XML data, is nowadays quite relevant also for geo-spatial data, due to their increasing usage in highly critical decisional processes. Among geo-spatial queries, those based on spatial and more precisely topological relations are currently used in an increasing number of applications. As far as we know, no approach has been proposed so far for relaxing queries based on topological predicates when they return an empty or insufficient answer, in order to improve result quality and user satisfaction. In this paper, we consider this problem and we present a general relaxation strategy for, possibly multi-domain, topological selection and join queries. Two specific semantics are also provided: the first applies the minimum amount of relaxation in order to get an acceptable answer; the second relaxes the given query of a certain fixed amount, depending on the considered topological predicate. Index-based processing algorithms, for efficiently executing relaxed queries based on the proposed semantics, are also presented and a specific topological similarity function, to be used for relaxation purposes, is proposed. Experimental results show that the overhead given by query relaxation is acceptable.