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Web Information Retrieval is another problem of searching elements of a set that are closest to a given query under a certain similarity criterion. It is of interest to take advantage of metric spaces in order to solve a search in an effective and efficient way. In this article, we present an extension of the M-Tree index, called XM-Tree, in order to improve search results. This index allows dynamic insertion of new data, reduces search costs using pruning and precalculated distances, and uses a tolerable amount of space, which makes this index apt for the extensive and dynamic Web. The proposed extension indexes Web documents, uses L2 as indexing distance and L∞ as similarity criterion to solve queries. We also present experiments validating the results.
Articles accepted for publication will be licensed under the Creative Commons BY-NC. Authors must sign a non-exclusive distribution agreement after article acceptance.
ISSN
1666-6038 (Online)
1666-6046 (Print)
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