Algorithmic Techniques for Massive Data Sets

Technical Report · Mon Apr 03 04:00:00 EDT 2006

DOI:https://doi.org/10.2172/881082· OSTI ID:881082

Charikar, Moses ^[1]

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1. Princeton University

This report describes the progress made during the Early Career Principal Investigator (ECPI) project on Algorithmic Techniques for Large Data Sets. Research was carried out in the areas of dimension reduction, clustering and finding structure in data, aggregating information from different sources and designing efficient methods for similarity search for high dimensional data. A total of nine different research results were obtained and published in leading conferences and journals.

• Research Organization: Princeton University
• Sponsoring Organization: USDOE - Office of Science (SC)
• DOE Contract Number: FG02-02ER25540
• OSTI ID: 881082
• Report Number(s): DOE/ER/25540
• Country of Publication: United States
• Language: English

Related Subjects

99 GENERAL AND MISCELLANEOUS
ALGORITHMS
DATA ANALYSIS
DATA BASE MANAGEMENT
INFORMATION RETRIEVAL
Massive Data Sets
Efficient Algorithms
dimension reduction
clustering
similarity search