R. Bliujute, C. Jensen, S. Saltenis and G. Slivinskas: "R-tree Based Indexing of Now-Relative Bitemporal Data", Proceedings 24th VLDB Conference, pp.345-356, New York, NY, 1998. ACM Computing Surveys, Vol. V, No. N, Month 20YY. 56 Yannis Manolopoulos et al. Home/Search Document Details and Download
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Efficient Processing of Spatiotemporal Queries in.. - Zimbrao, de Souza.. (2000) (Correct)
....for answering efficiently window queries for a number of consecutive images (spatiotemporal queries) The RST Tree provides support for both valid time and transaction time (bitemporal) spatial data, thus it is a more generic approach. It combines some ideas from R Trees [BKS 90] and GR Trees [BJSS98]. The kind of data that RST Trees indexes is different from the data indexed by the other structures mentioned before: it has two time dimensions, the valid time and the transaction time, plus the spatial extension. Also, since it is a very recent work we had no time to analyze it and include it ....
R. Bliujute, C. S. Jensen, S. Saltenis, G. Slivinskas: "R-Tree Based Indexing of Now-Relative Bitemporal Data". Proceedings of 24rd International Conference on Very Large Data Bases, New York City, New York, USA, August 24-27, 1998.
Light-Weight Indexing of General Bitemporal Data - Bliujute, Jensen, Saltenis.. (1998) (1 citation) Self-citation (Bliujute Jensen Saltenis Slivinskas) (Correct)
....the DBMS. This paper proposes an efficient bitemporal indexing technique that can be implemented as a layer on top of an existing DBMS, by an independent third party developer. In this sense, the index is light weight. There has recently been proposed a number of indices for temporal data (e.g. [3, 12, 13, 15, 16]; see [23] for a survey) The majority are for transaction time data, and only few support valid time data. Significantly less research has been done on creating indices for bitemporal data. Spatial indices are obvious candidates for indexing bitemporal data, due to the similarities between ....
....creating indices for bitemporal data. Spatial indices are obvious candidates for indexing bitemporal data, due to the similarities between bitemporal and spatial data: the combined valid and transaction time of a tuple can be treated as a region in two dimensional space. Several existing proposals [3, 12, 13] are based on the R tree [1] The bitemporal indices generally fall short in efficiently supporting now relative data [6] data for which the end of the valid time or and transaction time tracks the progressing current time. Now relative data occurs naturally in most real world databases. ....
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R. Bliujute, C. S. Jensen, S. Saltenis, and G. Slivinskas. Rtree Based Indexing of Now-Relative Bitemporal Data. Proceedings of VLDB, pp. 345--356, 1998.
Developing a DataBlade for a New Index - Bliujute, Saltenis, Slivinskas.. (1998) (13 citations) Self-citation (Bliujute Jensen Saltenis Slivinskas) (Correct)
....proposed by the research community, because these techniques can be integrated into DBMSs more easily. This facilitates dissemination of research results and the transition from research results to products. The paper describes a prototype implementation of a new access method, termed the GR tree [4], as an Informix DataBlade. Based on the R tree [3] an improved version of the R tree originally proposed by Guttman [7] this tree indexes now relative bitemporal data, which is data with associated valid time and transaction time values [14] Many real world databases contain a significant ....
....the bitemporal region stops growing (Tuples (2) 4) Cases 2, 4, 6) Two dimensional bitemporal regions can be indexed using adapted spatial indices. An essential challenge in indexing bitemporal data is to properly handle now relative intervals. The next section briefly presents the GR tree [4] which contends well with this requirement and outperforms other indices for now relative bitemporal data. A description of the implementation of the GR tree as an Informix DataBlade follows next. 3. The GR Tree Index The GR tree is based on the R tree [3] which is a spatial index consisting ....
[Article contains additional citation context not shown here]
R. Bliujute, C. S. Jensen, S. Saltenis, and G. Slivinskas. RTree Based Indexing of Now-Relative Bitemporal Data. Proceedings of VLDB, pp. 345--356 (1998).
R-Trees Have Grown Everywhere - Manolopoulos, Nanopoulos.. (Correct)
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R. Bliujute, C. Jensen, S. Saltenis and G. Slivinskas: "R-tree Based Indexing of Now-Relative Bitemporal Data", Proceedings 24th VLDB Conference, pp.345-356, New York, NY, 1998. ACM Computing Surveys, Vol. V, No. N, Month 20YY. 56 Yannis Manolopoulos et al.
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