Object Fusion in Geographic Information Systems Catriel Beeri, Yaron Kanza, Eliyahu Safra, and Yehoshua Sagiv   View Paper (PDF)   Return to RESEARCH SESSION 21:SIMILARITY SEARCH AND APPLICATIONS Abstract Given two geographic databases, a fusion algorithm should produce all pairs of corresponding objects (i.e., objects that represent the same real-world entity). Four fusion algorithms, which only use locations of objects, are described and their performance is measured in terms of recall and precision. These algorithms are designed to work even when locations are imprecise and each database represents only some of the real-world entities. Results of extensive experimentation are presented and discussed. The tests show that the performance depends on the density of the data sources and the degree of overlap among them. All four algorithms are much better than the current state of the art (i.e., the one-sided nearest-neighbor join). One of these four algorithms is best in all cases, at a cost of a small increase in the running time compared to the other algorithms. ©2005 Association for Computing Machinery