Performance Characterization of Data Mining Applications using MineBench ¨ . ıkyılmaz Gokhan Memik Alok Choudhary Joseph Zambreno Berkin Ozıs Department of Electrical Engineering and Computer Science Northwestern Uni

Source URL: www.bioperf.org

Spatial Cone Tree: An Index Structure for Correlation-based Similarity Queries on Spatial Time Series Data Pusheng Zhang, Shashi Shekhar, Vipin Kumar Computer Science & Engineering Department, University of Minnesota Ema

Source URL: www.cse.unt.edu

• Information retrieval
• Spatial database
• Nearest neighbor search
• Cone
• Data mining
• Geographic information system
• Conifer cone
• Information science
• R-tree
• Science

Information Integration Across Heterogeneous Sources: Where Do We Stand and How to Proceed? ∗ Aditya Telang and Sharma Chakravarthy and Yan Huang† IT Laboratory & Department of Computer Science & Engineering The Univ

Source URL: www.cse.unt.edu

• Data
• Computing
• Computer languages
• Database theory
• Data integration
• Federated database system
• Database
• Data mining
• Semantic Web
• Data management
• Database management systems
• Information

2005 Minerals Yearbook ARIZONA U.S. Department of the Interior U.S. Geological Survey

Source URL: minerals.er.usgs.gov

• Chemistry
• Pavements
• Stone
• Dietary minerals
• Transition metals
• Construction aggregate
• Molybdenum
• Copper extraction techniques
• Mining engineering
• Building materials
• Matter
• Construction

THE MINERAL INDUSTRY OF ARIZONA This chapter has been prepared under a Memorandum of Understanding between the U.S. Geological Survey and the Arizona Department of Mines and Mineral Resources for collecting information o

Source URL: minerals.er.usgs.gov

• Phelps Dodge
• Mining engineering
• Construction aggregate
• Copper
• Copper mining in Arizona
• Copper mining in the United States
• Matter
• Chemistry
• Mining

Information Engineering and Management (M.Sc.) Summer Term 2015 Long version SPO Department of Economics and Management

Source URL: www.wiwi.kit.edu

• Management
• Formal sciences
• Business
• Data mining
• Simulation
• Computer science
• Workflow
• Analytics
• Information systems
• Operations research
• Science
• Knowledge

THE MINERAL INDUSTRY OF MICHIGAN This chapter has been prepared under a Memorandum of Understanding between the U.S. Bureau of Mines, U.S. Department of the Interior, and the Geological Survey Division, Michigan Departme

Source URL: minerals.er.usgs.gov

• Architecture
• Stone
• Matter
• Concrete
• Natural materials
• Construction aggregate
• Crushed stone
• Mining engineering
• Mining
• Pavements
• Building materials
• Construction

POTENTIAL AND CONDITIONS FOR MINING THE TECHNOSPHERE Joakim KROOK, Nils JOHANSSON, Per FRÄNDEGÅRD Department of Management and Engineering, Environmental Technology and Management, Linköping University, SELink

Source URL: www.elfm.eu

Improving Digital Forensics Through Data Mining Chrysoula Tsochataridou, Avi Arampatzis, Vasilios Katos Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi, Greece

Source URL: www.aviarampatzis.com

• Data mining
• Cluster analysis
• Multivariate statistics
• Weka
• Text mining
• K-means clustering
• Email
• Enron
• Computer cluster
• Statistics
• Computing
• Data analysis

FIONA M. DOYLE Donald H. McLaughlin Professor of Mineral Engineering University of California, Berkeley Department of Materials Science and Engineering 210 Hearst Mining Building #1760

Source URL: www.mse.berkeley.edu