Abstract
Efficient processing of top-k queries on multidimensional grids is a common requirement in information retrieval and data mining, for example in OLAP cubes. We introduce a data structure, the K 2-treap, that represents grids in compact form and supports efficient prioritized range queries. We compare the K 2-treap with state-of-the-art solutions on synthetic and real-world datasets, showing that it uses 30% of the space of competing solutions while solving queries up to 10 times faster.
Keywords
- Real Dataset
- Range Query
- Synthetic Dataset
- Priority Queue
- Query Time
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Funded by Millennium Nucleus Information and Coordination in Networks ICM/FIC P10-024F, by a Conicyt scholarship, by MICINN (PGE and FEDER) TIN2009-14560-C03-02 and TIN2010-21246-C02-01, by CDTI, MEC and AGI EXP 00064563/ITC-20133062, and by Xunta de Galicia (with FEDER) GRC2013/053.
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Brisaboa, N.R., de Bernardo, G., Konow, R., Navarro, G. (2014). K 2-Treaps: Range Top-k Queries in Compact Space. In: Moura, E., Crochemore, M. (eds) String Processing and Information Retrieval. SPIRE 2014. Lecture Notes in Computer Science, vol 8799. Springer, Cham. https://doi.org/10.1007/978-3-319-11918-2_21
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DOI: https://doi.org/10.1007/978-3-319-11918-2_21
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11917-5
Online ISBN: 978-3-319-11918-2
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