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Erschienen in:
2013 | OriginalPaper | Buchkapitel
An Indexing Structure for Dynamic Multidimensional Data in Vector Space
verfasst von : Elena Mikhaylova, Boris Novikov, Anton Volokhov
Erschienen in: Advances in Databases and Information Systems
Verlag: Springer Berlin Heidelberg
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The multidimensional
k
–
NN
(
k
nearest neighbors) query problem is relevant to a large variety of database applications, including information retrieval, natural language processing, and data mining. To solve it efficiently, the database needs an indexing structure that provides this kind of search. However, attempts to find an exact solution are hardly feasible in multidimensional space. In this paper, a novel indexing technique for the approximate solution of
k
–
NN
problem is described and analyzed. The construction of the indexing tree is based on clustering. Indexing structure is implemented on top of high-performance industrial DBMS.