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Improved deletions in dynamic spatial approximation trees

G. Navarro, N. Reyes
23rd International Conference of the Chilean Computer Science Society, 2003. SCCC 2003. Proceedings.  
The Dynamic Spatial Approximation Tree (dsa-tree) is a recently proposed data structure for searching in metric spaces.  ...  However, it has been noted that deletions degrade the structure over time, so the structure cannot be regarded as fully dynamic in the sense that deletions are not sustainable for long periods of time.  ...  Dynamic Spatial Approximation Trees In this section we briefly describe dynamic sa-trees (dsa-trees for short) [8, 9, 10, 11 ].  ... 
doi:10.1109/sccc.2003.1245441 dblp:conf/sccc/NavarroR03 fatcat:47lx4qhsbvhr7hqv2ulzt27xxm

A Scientific On-line Database for Efficient Function Approximation [chapter]

Ivana Veljkovic, Paul E. Plassmann, Daniel C. Haworth
2003 Lecture Notes in Computer Science  
We observe significant improvements in cumulative time needed for database operations and memory requirements in a comparison of DOLFA to the function tabulation software system ISAT.  ...  In this paper we present several new algorithms which significantly improve the performance of software implementations of this database approach.  ...  The most significant improvement in running time and memory usage is observed with the dynamic cleaning of the database based on usage statistics.  ... 
doi:10.1007/3-540-44839-x_68 fatcat:q3qtrutdk5hufdf67me3anvvja

Dynamic and hierarchical spatial access method using integer searching

Kyoosang Cho, Yijie Han, Yugyung Lee, E. K. Park
2001 Proceedings of the tenth international conference on Information and knowledge management - CIKM'01  
In this paper, for a dynamic management of spatial objects, we construct a hierarchical dynamic data structure, called an IST/OPG hierarchy, which may overcome some limitations of existing Spatial Access  ...  For dynamic management of spatial objects in the IST/OPG hierarchy, a number of primary and supplementary operations are introduced.  ...  These operations improve efficiency in the searching [12] .  ... 
doi:10.1145/502585.502643 dblp:conf/cikm/ChoHLP01 fatcat:cjx3f6infjbyzlgs63swqmvxvi

Spatial Indexing for Location-Aware Systems

Robert K. Harle
2007 2007 Fourth Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services (MobiQuitous)  
It establishes the principles and requirements of a wide-area spatial indexer, reviews the R-tree, Quadtree and RQ-tree methods proposed before for indoor location-awareness, and significantly adapts the  ...  The proposed indexing method uses a combination of R-trees (for high level spatial information, down to structural level) and Quadtrees (for lower level representation of objects).  ...  The resultant scheme has been shown to be an improvement on previous attempts, and offers scope for further improvement.  ... 
doi:10.1109/mobiq.2007.4451027 dblp:conf/mobiquitous/Harle07 fatcat:xpsx5g2wznbj7dznhmukdkimsy

Parallel Batch-Dynamic kd-Trees [article]

Rahul Yesantharao
2021 arXiv   pre-print
In this paper, we present BDL-tree, a parallel, batch-dynamic implementation of a kd-tree that allows for efficient parallel k-NN queries over dynamically changing point sets.  ...  BDL-trees consist of a log-structured set of kd-trees which can be used to efficiently insert or delete batches of points in parallel with polylogarithmic depth.  ...  Vitter, “Bkd-tree: A under+dynamic+gas+mixtures. dynamic scalable kd-tree,” in International Symposium on Spatial and [35] J. Fonollosa, S. Sheik, R.  ... 
arXiv:2112.06188v1 fatcat:e5bje74lg5hbnlxanqkhubpqli

Decomposability of DiSAT for Index Dynamization

Edgar Chávez, María E. Di Genaro, Nora Susana Reyes, Patricia Roggero
2017 Journal of Computer Science and Technology  
The Distal Spatial Approximation Tree (DiSAT) is one of the most competitive indexes for exact proximity searching.  ...  On the other hand, there is an old approach from Bentley and Saxe (BS) allowing the dynamization of decomposable data structures. The only requirement is to provide a decomposition operation.  ...  Next, in Section 3 we detail the Distal Spatial Approximation Trees (DiSAT), and some notions of its close relatives: Spatial Approximation Trees (SAT) and the Dynamic Spatial Approximation Trees (DSAT  ... 
doi:10.24215/16666038.17.e15 fatcat:n5tpudjfardbbd54bgoa6ky26u

Indexing for Dynamic Abstract Regions

J. Jaffar, R.H.C. Yap, K.Q. Zhu
2006 22nd International Conference on Data Engineering (ICDE'06)  
These objects are "dynamic" and may have short life spans.  ...  This saves significant space for objects with large spatial extents since pre-segmentation is not needed.  ...  We are not aware of spatial structures that index the actual objects, as in RCtree. Furthermore, RC-tree's domain reduction technique, approximates sub-objects dynamically and on-demand.  ... 
doi:10.1109/icde.2006.81 dblp:conf/icde/JaffarYZ06 fatcat:zehct5ayx5b2dekwpjy7kb5nyy

LR-tree: a Logarithmic Decomposable Spatial Index Method

P. Bozanis
2003 Computer journal  
structures to dynamic ones onto R * -trees.  ...  In this paper, we present LR-trees, a new efficient scheme for dynamic manipulation of large datasets, which combines the search performance of the bulkloaded R-trees with the updated performance of R  ...  In other words, deletions operate in a quick-anddirty way, that does not improve the query performance asymptotically, but it does not degrade it either.  ... 
doi:10.1093/comjnl/46.3.319 fatcat:xrbkh3npjbagxgtwrmblane3ze

Multi-way R-tree joins using indirect predicates

H PARK
2004 Information and Software Technology  
Spatial join has been processed in two steps, called filter step and refinement step. The M-way R-tree join (MRJ) is a filter step join algorithm, which synchronously traverses M R-trees.  ...  Since spatial join processing consumes much time, several algorithms have been proposed to improve spatial join performance.  ...  We also examined how NMAX and EMAX can be dynamically maintained in conjunction with the R-tree insertion and deletion algorithms.  ... 
doi:10.1016/s0950-5849(04)00006-0 fatcat:2cve54yo55hdvpsuofqnvo5whi

Multi-way R-tree joins using indirect predicates

Ho-Hyun Park, Jun-Ki Min, Chin-Wan Chung, Tae-Gyu Chang
2004 Information and Software Technology  
Spatial join has been processed in two steps, called filter step and refinement step. The M-way R-tree join (MRJ) is a filter step join algorithm, which synchronously traverses M R-trees.  ...  Since spatial join processing consumes much time, several algorithms have been proposed to improve spatial join performance.  ...  We also examined how NMAX and EMAX can be dynamically maintained in conjunction with the R-tree insertion and deletion algorithms.  ... 
doi:10.1016/j.infsof.2003.12.007 fatcat:skebdzsctjfbhldnv72weaq36e

Efficient Indexing of Spatiotemporal Objects [chapter]

Marios Hadjieleftheriou, George Kollios, Vassilis J. Tsotras, Dimitrios Gunopulos
2002 Lecture Notes in Computer Science  
Better ways are thus needed to approximate general spatiotemporal objects.  ...  ., objects which change their position and/or extent over time appear in many applications. In this paper we examine the problem of indexing large volumes of such data.  ...  An Approximate Algorithm (MergeSplit) The dynamic programming algorithm is quadratic to the lifetime of the object.  ... 
doi:10.1007/3-540-45876-x_17 fatcat:y6kddpo6njek7ltq6cfozlzjfu

An incremental updating method for the kanonymous dataset using a similar-B-tree

Jinling Song, Liming Huang, Yan Gao, Haibin Liu
2017 Advances in Modelling and Analysis B  
This method can reflect the changes in the original dataset to the k-anonymous dataset in time, and it can greatly improve the update efficiency of the k-anonymous dataset.  ...  on the original dataset can be converted into the corresponding operations of leaf node in the similar-B-tree.  ...  However, the original dataset changes dynamically.  ... 
doi:10.18280/ama_b.600112 fatcat:ke6y4pwfn5enpmyczfsarqw4rq

An efficient and effective algorithm for density biased sampling

Alexandros Nanopoulos, Yannis Manolopoulos, Yannis Theodoridis
2002 Proceedings of the eleventh international conference on Information and knowledge management - CIKM '02  
It exploits spatial indexes and the local density information they preserve, to provide improved quality of sampling result and fast access to elements of the dataset.  ...  In this paper we describe a new density-biased sampling algorithm.  ...  Spatial indexes (like the R-tree [5] and variants) achieve a clustering of objects within their nodes, which preserves the local density information and can provide improved density approximations.  ... 
doi:10.1145/584857.584858 fatcat:cak5ncifbzamfoebk2m6msbq2a

An efficient and effective algorithm for density biased sampling

Alexandros Nanopoulos, Yannis Manolopoulos, Yannis Theodoridis
2002 Proceedings of the eleventh international conference on Information and knowledge management - CIKM '02  
It exploits spatial indexes and the local density information they preserve, to provide improved quality of sampling result and fast access to elements of the dataset.  ...  In this paper we describe a new density-biased sampling algorithm.  ...  Spatial indexes (like the R-tree [5] and variants) achieve a clustering of objects within their nodes, which preserves the local density information and can provide improved density approximations.  ... 
doi:10.1145/584792.584858 dblp:conf/cikm/NanopoulosMT02 fatcat:6ylea5ytwvbc3cuwnkpg5zavje

Evaluation of a Dynamic Tree Structure for Indexing Query Regions on Streaming Geospatial Data [chapter]

Quinn Hart, Michael Gertz, Jie Zhang
2005 Lecture Notes in Computer Science  
Our approach uses a Dynamic Cascade Tree (DCT ) to (1) index spatio-temporal query regions associated with continuous user queries and (2) efficiently determine what incoming RSI data is relevant to what  ...  The DCT exploits spatial trends in incoming RSI data to efficiently filter the data of interest to the individual query regions.  ...  These trees are simple to maintain dynamically in O(n) space.  ... 
doi:10.1007/11535331_9 fatcat:cucbl4gryretxkmhiudjuodse4
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