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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)
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)
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