RRSi: indexing XML data for proximity twig queries
Knowledge and Information Systems
Effectiveness of NAQ-tree as index structure for similarity search in high-dimensional metric space
Knowledge and Information Systems
Bulk construction of dynamic clustered metric trees
Knowledge and Information Systems
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Databases are getting more and more important for storing complex objects from scientific, engineering, or multimedia applications. Examples for such data are chemical compounds, CAD drawings, or XML data. The efficient search for similar objects in such databases is a key feature. However, the general problem of many similarity measures for complex objects is their computational complexity, which makes them unusable for large databases. In this paper, we combine and extend the two techniques of metric index structures and multi-step query processing to improve the performance of range query processing. The efficiency of our methods is demonstrated in extensive experiments on real-world data including graphs, trees, and vector sets.