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» Practical Preference Relations for Large Data Sets
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APVIS
2007
13 years 10 months ago
Interpreting large visual similarity matrices
Visual similarity matrices (VSMs) are a common technique for visualizing graphs and other types of relational data. While traditionally used for small data sets or well-ordered la...
Christopher Mueller, Benjamin Martin, Andrew Lumsd...
APWEB
2004
Springer
14 years 1 months ago
Using Relational Database Constraints to Design Materialized Views in Data Warehouses
Queries to data warehouses often involve hundreds of complex aggregations over large volumes of data, and so it is infeasible to compute these queries by scanning the data sources ...
Taehee Lee, Jae-young Chang, Sang-goo Lee
CAISE
1999
Springer
14 years 22 days ago
A Practical Approach to Access Heterogeneous and Distributed Databases
A common problem within most large corporations nowadays is the diversity of database systems that are employed by their many departments in the development of a product. Usually, ...
Fernando de Ferreira Rezende, Ulrich Hermsen, Geor...
ACSAC
2008
IEEE
13 years 10 months ago
Practical Applications of Bloom Filters to the NIST RDS and Hard Drive Triage
Much effort has been expended in recent years to create large sets of hash codes from known files. Distributing these sets has become more difficult as these sets grow larger. Mea...
Paul F. Farrell Jr., Simson L. Garfinkel, Douglas ...
JMLR
2010
135views more  JMLR 2010»
13 years 3 months ago
An Exponential Model for Infinite Rankings
This paper presents a statistical model for expressing preferences through rankings, when the number of alternatives (items to rank) is large. A human ranker will then typically r...
Marina Meila, Le Bao