Handbook of Massive Data Sets

Pirmais vāks
James Abello, Panos M. Pardalos, Mauricio G.C. Resende
Springer Science & Business Media, 2002. gada 31. marts - 1223 lappuses
The proliferation of massive data sets brings with it a series of special computational challenges. This "data avalanche" arises in a wide range of scientific and commercial applications. With advances in computer and information technologies, many of these challenges are beginning to be addressed by diverse inter-disciplinary groups, that indude computer scientists, mathematicians, statisticians and engineers, working in dose cooperation with application domain experts. High profile applications indude astrophysics, bio-technology, demographics, finance, geographi cal information systems, government, medicine, telecommunications, the environment and the internet. John R. Tucker of the Board on Mathe matical Seiences has stated: "My interest in this problern (Massive Data Sets) isthat I see it as the rnost irnportant cross-cutting problern for the rnathernatical sciences in practical problern solving for the next decade, because it is so pervasive. " The Handbook of Massive Data Sets is comprised of articles writ ten by experts on selected topics that deal with some major aspect of massive data sets. It contains chapters on information retrieval both in the internet and in the traditional sense, web crawlers, massive graphs, string processing, data compression, dustering methods, wavelets, op timization, external memory algorithms and data structures, the US national duster project, high performance computing, data warehouses, data cubes, semi-structured data, data squashing, data quality, billing in the large, fraud detection, and data processing in astrophysics, air pollution, biomolecular data, earth observation and the environment.

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Saturs

Algorithmic Aspects of Information Retrieval on the Web
3
HighPerformance Web Crawling
25
Internet Growth Is There a Moores Law For Data Traffic?
47
MASSIVE GRAPHS
95
Random Evolution in Massive Graphs
97
Property Testing in Massive Graphs
123
STRING PROCESSING AND DATA COMPRESSION
149
String Pattern Matching for a Deluge Survival Kit
151
Data Squashing Constructing Summary Data Sets
579
Mining and Monitoring Evolving Data
593
Data Quality in Massive Data Sets
643
Data Warehousing
661
Aggregate View Management in Data Warehouses
711
Semistructured Data and XML
743
ARCHITECTURE ISSUES
789
Overview of High Performance Computers
791

Searching Large Text Collections
195
Data Compression
245
EXTERNAL MEMORY ALGORITHMS AND DATA STRUCTURES
311
External Memory Data Structures
313
External Memory Algorithms
359
OPTIMIZATION
417
Data Envelopment Analysis DEA in Massive Data Sets
419
Optimization Methods in Massive Data Sets
439
Wavelets and Mutiscale Transforms in Astronomical Image Processing
473
Clustering in Massive Data Sets
501
DATA MANAGEMENT
545
Managing and Analyzing Massive Data Sets with Data Cubes
547
The National Scalable Cluster Project
851
Sorting and Selection on Parallel Disk Models
873
APPLICATIONS
891
Billing in the Large
893
Detecting Fraud in the Real World
909
Massive Datasets in Astronomy
929
Data Management in Environmental information Systems
979
Massive Data Sets Issues in Earth Observing
1091
Mining Biomolecular Data Using Background Knowledge and Artificial Neural Networks
1139
Massive Data Set Issues in Air Pollution Modelling
1167
INDEX
1218
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