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Range queries in metric spaces have applications in many areas such as multimedia retrieval, computational biology, and location-based services, where metric uncertain data exists in different forms, resulting from equipment limitations, high-throughput sequencing technologies, privacy preservation, or others. In this paper, we represent metric uncertain(More)
The goal in similarity search is to find objects similar to a specified query object given a certain similarity criterion. Although useful in many areas, such as multimedia retrieval, pattern recognition, and computational biology, to name but a few, similarity search is not yet supported well by commercial DBMS. This may be due to the complex data types(More)
Given two object sets $$P$$ P and $$Q$$ Q , a k-closest pair $$(k\hbox {CP})$$ ( k CP ) query finds $$k$$ k closest object pairs from $$P\times Q$$ P × Q . This operation is common in many real-life applications such as GIS, data mining, and recommender systems. Although it has received much attention in the Euclidean space, there is little prior work on(More)
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