Handbook of Massive Data Sets

• Άλλοι συγγραφείς: Abello, James (Επιμελητής έκδοσης), Pardalos, Panos M. (Επιμελητής έκδοσης), Resende, Mauricio G. C. (Επιμελητής έκδοσης)
• Μορφή: Βιβλίο
• Έκδοση: Dordrecht, The Netherlands Kluwer Academic Publishers c2002
• Σειρά: Massive Computing
• Θέματα: HANDBOOK

Πίνακας περιεχομένων:

• Contents : Preface, Part I : Internet and the World Wide Web : 1. Algorithmic Aspects of Information Retrieval on the Web, 2. High-Performance Web Crawling, 3. Internet Growth: is there a "Moore's Law" for Data Traffic, Part II : Massive Graphs : 4. Random Evolution in Massive Graphs, 5. Property Testing in Massive Graphs, Part III : 6. String Pattern Matching for a Deluge Survival Kit, 7. Searching Large Text Collections, 8. Data Compression, Part IV : External memory algorithms and Data Structures : 9. External Memory Data Structures, 10. External Memory Algorithms, Part V : Optimization : 11. Data Envelopment Analysis (DEA) in Massive Data Sets, 12. Optimization Methods in Massive Data Sets, 13. Wavelets and Multiscale Transforms in Astronomical Image Processing, 14. Clustering in Massive Data Sets, Part VI : Data Management : 15. Managing and Analyzing Massive Data Sets with Data Cubes, 16. Data Squashing : Constructing Summary Data Sets, 17. Mining and Monitoring Evoling Data, 18. Data Quality in Massive Data Sets, 19. Data Warehousing, 20. Aggregate View Management in Data Warehouses, 21. Semistructured Data and XML, Part VII : Architecture Issues : 22. Overview of High Performance Computers, 23. The National Scalable Cluster Project, 24. Sorting and Selection on Parallel Disk Models, Part VIII : Applications : 25. Billing in the Large, 26. Detecting Fraud in the Real World, 27. Massive Datasets in Astronomy, 28. Data Management in environmental Information Systems, 29. Massive Data Sets Issues in Earth Observing, 30. Mining Biomolecular Data Using Background Knowledge and Artificial neural Networks, 31. Massive Data Set Issues in Air Pollution Modelling, Index