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## Extending an Index-Benchmarking Framework with Non-Invasive Visualization Capability

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### Citations

2713 | R-trees: a dynamic index structure for spatial searching
- Guttman
- 1984
(Show Context)
Citation Context ...nate regions. This builds a hierarchical tree structure. With this, the complexity should decrease from O(n) to O(log(n)) for point search. An important multi-dimensional tree technique is the R-Tree =-=[Gut84]-=- as well as its derivates R +-Tree [SRF87] and R∗-Tree [BKSS90]. In Figure 1, we visualize the SS-Tree [WJ96] using multi-dimensional spheres and the SR-Tree [KS97] whose regions are the intersection ... |

1369 | An overview of aspectj - Kiczales, Hilesdale, et al. - 2001 |

1243 | B.: ‘The R*-tree: An Efficient and Robust Access Method for Points and Rectangles
- Beckmann, Kriegel, et al.
- 1990
(Show Context)
Citation Context ... this, the complexity should decrease from O(n) to O(log(n)) for point search. An important multi-dimensional tree technique is the R-Tree [Gut84] as well as its derivates R+-Tree [SRF87] and R∗-Tree =-=[BKSS90]-=-. In Figure 1, we visualize the SS-Tree [WJ96] using multi-dimensional spheres and the SR-Tree [KS97] whose regions are the intersection between a multi-dimensional sphere and rectangle. However, tree... |

1001 | Approximate nearest neighbors: towards removing the curse of dimensionality
- Indyk, Motwani
- 1998
(Show Context)
Citation Context ... helpful to see neighboring regions in the space-filling curve and whether all of them are evaluated. Hashing Methods. As a hashing method for multi-dimensional data, Locality Sensitive Hashing (LSH) =-=[IM98]-=- is most often used, because they support nearest neighbor queries. LSH uses locality sensitive functions to set up several hash tables with the constraint that all points in one bucket should, with a... |

678 | Multidimensional access methods
- Gaede, Günther
- 1998
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Citation Context ...crime scene latent fingerprint scans are executed [KFV11]. These fingerprints are stored in a database to find possible suspects. Querying a fingerprint database bears challenges, e.g. given workload =-=[GG98]-=-, data dimensionality and used query types [GBS + 12]. These challenges are addressed by multi-dimensional index structures. Numerous multi-dimensional index structures are introduced [GG98, Sam05], b... |

617 | A Quantitative Analysis and Performance Study for Similaritysearch Methods
- Weber, Schek, et al.
- 1942
(Show Context)
Citation Context ... curse of dimensionality, which says that at a certain dimensionality (for tree techniques ca. 26), the nearest neighbor query performance of an index structure will be worse than a sequential search =-=[WSB98]-=-. Thus, a visualization of the query execution would be helpful to show these deficits. When visualizing the partitioning scheme, it is important to have a good representation for the hierarchy. Since... |

506 | Locality-sensitive hashing scheme based on p-stable distributions,” the 12th annual symposium on Computational geometry
- Datar, Immorlica, et al.
- 2004
(Show Context)
Citation Context ...hould, with a high probability, be locally nearer to each other than to any point in another bucket. With this constraint, neighborship relations are preserved. Promising LSH methods are p-stable LSH =-=[DIIM04]-=- whose partitioning looks similar to stairs and the permutation approach [CGFN08]. Since hashing methods use several hash tables, a visualization of several partitionings is necessary. 3 Requirements ... |

437 | The SR-tree: An index structure for highdimensional nearest neighbor queries
- Katayama, Satoh
- 1997
(Show Context)
Citation Context ...ional tree technique is the R-Tree [Gut84] as well as its derivates R +-Tree [SRF87] and R∗-Tree [BKSS90]. In Figure 1, we visualize the SS-Tree [WJ96] using multi-dimensional spheres and the SR-Tree =-=[KS97]-=- whose regions are the intersection between a multi-dimensional sphere and rectangle. However, tree techniques suffer from the curse of dimensionality, which says that at a certain dimensionality (for... |

386 | Foundations of Multidimensional and Metric Data Structures - Samet - 2006 |

344 | Similarity indexing with the SS-tree
- White, Jain
- 1996
(Show Context)
Citation Context ...o O(log(n)) for point search. An important multi-dimensional tree technique is the R-Tree [Gut84] as well as its derivates R +-Tree [SRF87] and R∗-Tree [BKSS90]. In Figure 1, we visualize the SS-Tree =-=[WJ96]-=- using multi-dimensional spheres and the SR-Tree [KS97] whose regions are the intersection between a multi-dimensional sphere and rectangle. However, tree techniques suffer from the curse of dimension... |

341 | The R+-Tree: A Dynamic Index for MultiDimensional Objects
- Sellis, Roussopoulos, et al.
- 1987
(Show Context)
Citation Context ...ree structure. With this, the complexity should decrease from O(n) to O(log(n)) for point search. An important multi-dimensional tree technique is the R-Tree [Gut84] as well as its derivates R +-Tree =-=[SRF87]-=- and R∗-Tree [BKSS90]. In Figure 1, we visualize the SS-Tree [WJ96] using multi-dimensional spheres and the SR-Tree [KS97] whose regions are the intersection between a multi-dimensional sphere and rec... |

317 | Information visualization and visual data mining
- Keim
(Show Context)
Citation Context ...vertheless, we cannot use an approximation of the data, because the partitioning schema relies on a multi-dimensional vector space. Changing the visualization paradigm (a collection can be found here =-=[Kei02]-=-) would destroy the relation between data and the corresponding partitioning scheme of the index structure. 2 http://wwwiti.cs.uni-magdeburg.de/iti db/research/iJudge/index en.php(a.1), (a.3). To vis... |

163 | Fractals for secondary key retrieval
- Faloutsos, Roseman
- 1989
(Show Context)
Citation Context ...ion, which is constructed iteratively assigning a one dimensional value to each indexed region. Typical space-filling curves are the Z-Curve [OM84], used in the UB-Tree [Bay97], and the Hilbert-Curve =-=[FR89]-=-. Considering nearest neighbor queries, it is helpful to see neighboring regions in the space-filling curve and whether all of them are evaluated. Hashing Methods. As a hashing method for multi-dimens... |

162 |
A class of data structures for associative searching
- Orenstein, Merrett
- 1983
(Show Context)
Citation Context ...lling curves. A space-filling curve is a mathematical function, which is constructed iteratively assigning a one dimensional value to each indexed region. Typical space-filling curves are the Z-Curve =-=[OM84]-=-, used in the UB-Tree [Bay97], and the Hilbert-Curve [FR89]. Considering nearest neighbor queries, it is helpful to see neighboring regions in the space-filling curve and whether all of them are evalu... |

120 | Visdb: Database exploration using multidimensional visualization
- Keim, Kriegel
- 1994
(Show Context)
Citation Context ...rogrammer of the index structure has to provide the necessary AspectJ modules for each index structure that has to be visualized. 7 Related Work Related work has already been done by Keim and Kriegel =-=[KK94]-=-. With VisDB, they introduce a system for an exploration of databases. They present their own visualization paradigm using grouping and transformation of the data into a two-dimensional screen to have... |

112 | Rolling the dice: Multidimensional visual exploration using scatterplot matrix navigation
- Elmqvist, Dragicevic, et al.
(Show Context)
Citation Context ... we use a scatterplot matrix. A scatterplot is the visual representation of a Cartesian space where the data points are arranged. Although 3D-Scatterplots can be extended using color, shape, and size =-=[EDF08]-=-, a single scatterplot does not suffice our requirements for visualizing multidimensional data. To solve this problem, we use a scatterplot matrix having the dimensions as rows and columns. Each entry... |

106 |
The universal B-Tree for multidimensional Indexing: General Concepts
- Bayer
- 1997
(Show Context)
Citation Context ...g curve is a mathematical function, which is constructed iteratively assigning a one dimensional value to each indexed region. Typical space-filling curves are the Z-Curve [OM84], used in the UB-Tree =-=[Bay97]-=-, and the Hilbert-Curve [FR89]. Considering nearest neighbor queries, it is helpful to see neighboring regions in the space-filling curve and whether all of them are evaluated. Hashing Methods. As a h... |

44 | A scalable framework for information visualization
- Kreuseler, Lpez, et al.
(Show Context)
Citation Context ...less, we cannot transform the data, because the relation between data and the corresponding partitioning scheme would be destroyed. Another important visualization framework is the scalable framework =-=[KLS00]-=-. Since there is a limited number of objects that can be visualized, the authors propose several techniques, such as Self-Organizing Maps or Magic Eye View to represent high amounts of data points. Su... |

40 | Anti-persistence: History independent data structures
- Naor, Teague
- 2001
(Show Context)
Citation Context ...entation arises to examine the partitioning scheme and to derive deficits [GBS + 12]. Furthermore, the sequence of operations (e.g. inserts and updates) influence the partitioning of index structures =-=[NT01]-=-. Thus, two different sequences performing the same operations lead to different structures. In summary, such a visualization component shall, for instance help engineers to decide whether identified ... |

33 | Effective Proximity Retrieval by Ordering Permutations
- Gonzalez, Figueroa, et al.
(Show Context)
Citation Context ... in another bucket. With this constraint, neighborship relations are preserved. Promising LSH methods are p-stable LSH [DIIM04] whose partitioning looks similar to stairs and the permutation approach =-=[CGFN08]-=-. Since hashing methods use several hash tables, a visualization of several partitionings is necessary. 3 Requirements for a Visualization Component For our visualization component, we divide the requ... |

20 | An approximation-based data structure for similarity search
- Weber, Blott
- 1997
(Show Context)
Citation Context ...quential search are introduced which compare every data point with the query. The optimization is often an approximation of the actual data points to reduce comparison costs. For example, the VA-File =-=[WB97]-=- splits the whole space into cells(a) S1 S4 S7 (b) RS1 RS4 RS7 S5 S6 S2 S8 RS5 RS6 RS2 RS8 S11 S10 A B S9 C RS11 RS10 A RS9 B C S12 RS3 RS12 S3 Figure 1: (a) SS-Tree, (b) SR-Tree and assigns a unique... |

6 | An OverviewofAspectJ - Kiczales, Hilsdale, et al. - 1995 |

3 |
Latent fingerprint detection using a spectral texture feature
- Kiertscher, Fischer, et al.
- 2011
(Show Context)
Citation Context ...ering of complex solutions. 1 Introduction Modern forensic investigation makes increasing use of digitally stored evidences. For this purpose, on the crime scene latent fingerprint scans are executed =-=[KFV11]-=-. These fingerprints are stored in a database to find possible suspects. Querying a fingerprint database bears challenges, e.g. given workload [GG98], data dimensionality and used query types [GBS + 1... |

3 |
Sylvie PhilippFoliguet, “High-dimensional descriptor indexing for large multimedia databases
- Valle, Cord
(Show Context)
Citation Context ...apping so that multiple paths have to be taken while evaluating a query. (a.4) An important role is to support different dimensions. Since multi-dimensional data implies a dimensionality of up to 100 =-=[VCPF08]-=-, we also have to be able to visualize all of these dimensions and dependencies between them. 3.2 Software Requirements Considering the implementation, we define the following requirements: (b.1) no a... |

2 |
The R+-Tree: ADynamic Index for Multi-Dimensional Objects
- Sellis, Roussopoulos, et al.
- 1987
(Show Context)
Citation Context ... tree structure. With this, the complexity should decrease from O(n) to O(log(n)) for point search. An important multi-dimensional tree technique is the R-Tree [Gut84]aswell as its derivates R +-Tree =-=[SRF87]-=-and R∗-Tree [BKSS90]. In Figure 1, we visualize the SS-Tree [WJ96] using multi-dimensional spheres and the SR-Tree [KS97] whose regions are the intersection between amulti-dimensional sphere and recta... |

1 |
and TimH.Merrett. Aclass of data structures for associative searching
- Orenstein
- 1984
(Show Context)
Citation Context ...ace-filling curves. A space-filling curveisamathematical function, which is constructed iteratively assigning aone dimensional value to each indexedregion. Typical space-filling curves are the Z-Curve=-=[OM84]-=-, used in the UB-Tree [Bay97], and the Hilbert-Curve[FR89]. Considering nearest neighbor queries, it is helpful to see neighboring regions in the space-filling curve and whether all of them are evalua... |