目前的关联规则挖掘算法主要依靠基于支持度的剪切策略来减小组合搜索空间.如果挖掘潜在的令人感兴趣的低支持度模式,这种策略并非有效.为此,提出一种新的关联模式—可信关联规则(credible association rule,简称CAR),规则中每个项目的...目前的关联规则挖掘算法主要依靠基于支持度的剪切策略来减小组合搜索空间.如果挖掘潜在的令人感兴趣的低支持度模式,这种策略并非有效.为此,提出一种新的关联模式—可信关联规则(credible association rule,简称CAR),规则中每个项目的支持度处于同一数量级,规则的置信度直接反映其可信程度,从而可以不必再考虑传统的支持度.同时,提出MaxcliqueMining算法,该算法采用邻接矩阵产生2-项可信集,进而利用极大团思想产生所有可信关联规则提出并证明了几个相关命题以说明这种规则的特点及算法的可行性和有效性.在告警数据集及Pumsb数据集上的实验表明,该算法挖掘CAR具有较高的效率和准确性.展开更多
A remarkable connection between the clique number and the Lagrangian of a graph was established by Motzkin and Straus. Later, Rota Bul′o and Pelillo extended the theorem of Motzkin-Straus to r-uniform hypergraphs by ...A remarkable connection between the clique number and the Lagrangian of a graph was established by Motzkin and Straus. Later, Rota Bul′o and Pelillo extended the theorem of Motzkin-Straus to r-uniform hypergraphs by studying the relation of local（global） minimizers of a homogeneous polynomial function of degree r and the maximal（maximum） cliques of an r-uniform hypergraph. In this paper, we study polynomial optimization problems for non-uniform hypergraphs with four different types of edges and apply it to get an upper bound of Tur′an densities of complete non-uniform hypergraphs.展开更多
Coloring the nodes of a graph is a commonly used technique to speed up clique search algorithms. Coloring the edges of the graph as a preconditioning method can also be used to speed up computations. In this paper we ...Coloring the nodes of a graph is a commonly used technique to speed up clique search algorithms. Coloring the edges of the graph as a preconditioning method can also be used to speed up computations. In this paper we will show that an unconventional coloring scheme of the edges leads to an NP-complete problem when one intends to determine the optimal number of colors.展开更多
文摘目前的关联规则挖掘算法主要依靠基于支持度的剪切策略来减小组合搜索空间.如果挖掘潜在的令人感兴趣的低支持度模式,这种策略并非有效.为此,提出一种新的关联模式—可信关联规则(credible association rule,简称CAR),规则中每个项目的支持度处于同一数量级,规则的置信度直接反映其可信程度,从而可以不必再考虑传统的支持度.同时,提出MaxcliqueMining算法,该算法采用邻接矩阵产生2-项可信集,进而利用极大团思想产生所有可信关联规则提出并证明了几个相关命题以说明这种规则的特点及算法的可行性和有效性.在告警数据集及Pumsb数据集上的实验表明,该算法挖掘CAR具有较高的效率和准确性.
基金Supported by the National Natural Science Foundation of China(No.11671124)
文摘A remarkable connection between the clique number and the Lagrangian of a graph was established by Motzkin and Straus. Later, Rota Bul′o and Pelillo extended the theorem of Motzkin-Straus to r-uniform hypergraphs by studying the relation of local（global） minimizers of a homogeneous polynomial function of degree r and the maximal（maximum） cliques of an r-uniform hypergraph. In this paper, we study polynomial optimization problems for non-uniform hypergraphs with four different types of edges and apply it to get an upper bound of Tur′an densities of complete non-uniform hypergraphs.
文摘Coloring the nodes of a graph is a commonly used technique to speed up clique search algorithms. Coloring the edges of the graph as a preconditioning method can also be used to speed up computations. In this paper we will show that an unconventional coloring scheme of the edges leads to an NP-complete problem when one intends to determine the optimal number of colors.
