A fair assignment algorithm for multiple preference queries
Proceedings of the VLDB Endowment
Optimal matching between spatial datasets under capacity constraints
ACM Transactions on Database Systems (TODS)
Top-K probabilistic closest pairs query in uncertain spatial databases
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Evaluating probabilistic spatial-range closest pairs queries over uncertain objects
WAIM'11 Proceedings of the 12th international conference on Web-age information management
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Given two datasets $A$ and $B$, their exclusive closest pairs (ECP) join is a one-to-one assignment of objects from the two datasets, such that (i) the closest pair $(a,b)$ in $A \times B$ is in the result and (ii) the remaining pairs are determined by removing objects $a,b$ from $A,B$ respectively, and recursively searching for the next closest pair. A real application of exclusive closest pairs is the computation of (car, parking slot) assignments. This paper introduces the problem and proposes several solutions that solve it in main-memory, exploiting space partitioning. In addition, we define a dynamic version of the problem, where the objective is to continuously monitor the ECP join solution, in an environment where the joined datasets change positions and content. Finally, we study an extended form of the query, where objects in one of the two joined sets (e.g., parking slots) have a capacity constraint, allowing them to match with multiple objects from the other set (e.g., cars). We show how our techniques can be extended for this variant and compare them with a previous solution to this problem. Experimental results on a system prototype demonstrate the efficiency and applicability of the proposed algorithms.