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Fundamentals of Database Indexing and Searching

Arnab Bhattacharya
€179.80
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A01=Arnab Bhattacharya
Actual Data Objects
advanced data structures
Aggregation Queries over Multiple Attributes
answer
Author_Arnab Bhattacharya
Basic Model of a Database
binary
Binary Search Tree
Category=PBT
Category=UN
Category=UNF
Category=UY
computational geometry
Data Reduction
database queries
Dimensionality Reduction
disk
Disk Page
Disk-Based Index Structures
Distance Function
efficient similarity query techniques
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eq_isMigrated=2
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Grid Cell
high dimensional data retrieval
Higher End Point
Index Structure
index structures for low- and high-dimensional spaces
Left Subtree
MBR
Memory-Based Index Structures
metric space indexing
multidimensional search algorithms
pages
Pairwise Distances
point
Point Query
query
Query Object
Query Range
Query Rectangle
Query Region
range
Range Search
retrieve information from massive data collections
Roc Curve
set
Similarity Search
similarity search queries
Space Filling Curve
spatial data analysis
Split Pointer
structure
Suffix Tree
tree
Triangular Inequality
Vice Versa
Voronoi Diagram

Product details

  • ISBN 9781466582545
  • Weight: 544g
  • Dimensions: 156 x 234mm
  • Publication Date: 02 Dec 2014
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description

Fundamentals of Database Indexing and Searching presents well-known database searching and indexing techniques. It focuses on similarity search queries, showing how to use distance functions to measure the notion of dissimilarity.

After defining database queries and similarity search queries, the book organizes the most common and representative index structures according to their characteristics. The author first describes low-dimensional index structures, memory-based index structures, and hierarchical disk-based index structures. He then outlines useful distance measures and index structures that use the distance information to efficiently solve similarity search queries. Focusing on the difficult dimensionality phenomenon, he also presents several indexing methods that specifically deal with high-dimensional spaces. In addition, the book covers data reduction techniques, including embedding, various data transforms, and histograms.

Through numerous real-world examples, this book explores how to effectively index and search for information in large collections of data. Requiring only a basic computer science background, it is accessible to practitioners and advanced undergraduate students.

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