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Parallel Data Mining for Association Rules on Shared-Memory Systems
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Mining generalized association rules
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Compile-Time Scheduling Algorithms for a Heterogeneous Network of Workstations
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Efficient mining of association rules in distributed databases
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Parallel mining of association rules
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Mining association rules: anti-skew algorithms
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An efficient approach to discovering knowledge from large databases
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Hash based parallel algorithms for mining association rules
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A fast distributed algorithm for mining association rules
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Evaluation of sampling for data mining of association rules
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Software caching on cache-coherent multiprocessors
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Design and evaluation of a compiler algorithm for prefetching
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Global optimizations for parallelism and locality on scalable parallel machines
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Improving the cache locality of memory allocation
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Mining association rules between sets of items in large databases
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Compiler optimizations for improving data locality
inferredcites →https://doi.org/10.1145/207110.207145openalex-snapshot
Unifying data and control transformations for distributed shared-memory machines
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Data and computation transformations for multiprocessors
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Efficient parallel data mining for association rules
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An effective hash-based algorithm for mining association rules
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Compiler cache optimizations for banded matrix problems
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Mining quantitative association rules in large relational tables
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Compiler-based prefetching for recursive data structures
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Dynamic itemset counting and implication rules for market basket data
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Scalable parallel data mining for association rules
inferredcites →https://doi.org/10.1145/258492.258524openalex-snapshot
A localized algorithm for parallel association mining
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Parallel data mining for association rules on shared-memory multi-processors
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An efficient algorithm for heap storage allocation
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The Art of Computer Programming. Volume 1: Fundamental Algorithms.
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