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N-list and B-list have simply been proven to be highly effective for mining frequent itemsets. The main problem of the two novel structures is that they both need to encode each node of pre-order (or start order) and post-order (or finish order) code. This causes excessive memory consumption to mine frequent itemsets. In this paper, we propose SO-Sets based(More)
  • Long Tan
  • 2015
Because of the shortcomings of the traditional K-means algorithm which is sensitive to select the initial clustering centers and easy converges to local optimization, the paper proposes An Clustering K-means Algorithm Based on Improved the Particle Swarm Optimization Algorithm. The algorithm uses a powerful global search capability of the Particle Swarm(More)
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