.png){kind=icon}
Return
Multidimensional access methods
.png){kind=icon}
OA
AI
DOI：10.1145/280277.280279.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Search operations in databases require special support at the physical level. This is true for conventional databases as well as spatial databases, where typical search operations include the point query (find all objects that contain a given search point) and the region query (find all objects that overlap a given search region). More than ten years of spatial database research have resulted in a great variety of multidimensional access methods to support such operations. We give an overview of that work. After a brief survey of spatial data management in general, we first present the class of point access methods, which are used to search sets of points in two or more dimensions. The second part of the paper is devoted to spatial access methods to handle extended objects, such as rectangles or polyhedra. We conclude with a discussion of theoretical and experimental results concerning the relative performance of various approaches.
Keywords:
data structures
multidimensional access methods
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
28
Papers:
2.4K
Citations:
3.5W
Organization
No organization information available
Cited Papers
.png){kind=icon}
Fluorescence-Quenched Substrates for Quantitative Live Cell Imaging of Glucocerebrosidase Activity
PREAI
ShareSaveShareSaveShareSaveShareSave
View more