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SIGMOD
2001
ACM
200views Database» more  SIGMOD 2001»
14 years 10 months ago
Data Bubbles: Quality Preserving Performance Boosting for Hierarchical Clustering
In this paper, we investigate how to scale hierarchical clustering methods (such as OPTICS) to extremely large databases by utilizing data compression methods (such as BIRCH or ra...
Markus M. Breunig, Hans-Peter Kriegel, Peer Kr&oum...
PODS
2001
ACM
127views Database» more  PODS 2001»
14 years 10 months ago
Optimal Aggregation Algorithms for Middleware
Assume that each object in a database has m grades, or scores, one for each of m attributes. For example, an object can have a color grade, that tells how red it is, and a shape g...
Ronald Fagin, Amnon Lotem, Moni Naor
MFCS
2001
Springer
14 years 2 months ago
News from the Online Traveling Repairman
In the traveling repairman problem (Trp), a tour must be found through every one of a set of points (cities) in some metric space such that the weighted sum of completion times of ...
Sven Oliver Krumke, Willem de Paepe, Diana Poensge...
IJCAI
2001
13 years 11 months ago
Solving Non-Boolean Satisfiability Problems with Stochastic Local Search
Much excitement has been generated by the success of stochastic local search procedures at finding solutions to large, very hard satisfiability problems. Many of the problems on wh...
Alan M. Frisch, Timothy J. Peugniez
ICCAD
2001
IEEE
192views Hardware» more  ICCAD 2001»
14 years 6 months ago
BOOM - A Heuristic Boolean Minimizer
We present a two-level Boolean minimization tool (BOOM) based on a new implicant generation paradigm. In contrast to all previous minimization methods, where the implicants are ge...
Jan Hlavicka, Petr Fiser