Discovering cyclic generalized association rules from transaction datbases can reveal the relationship of differ-ent levels of the taxonomies and display cyclic variations over time.Information about such variations i...Discovering cyclic generalized association rules from transaction datbases can reveal the relationship of differ-ent levels of the taxonomies and display cyclic variations over time.Information about such variations is great use of better identifying trends in associations and forecast-ing.Because cyclic rules are quite sensitive to a littlenoise,this paper uses the noise-ratio as the criterion of i-dentifing cydclic itemsets for dealing with the problem and utilizes the cycle-pruning technique to reduce the comput-ing time of the data mining process by exploiting the real-tionship between the cycle and generalized frequent item-sets.The paper gives the algorithm of mining cyclic gen-eralized itemsets(CGI).Experiment shows that the CGI algorithm can efficiently yield results.展开更多
Judice and Pires developed in recent years principal pivoting methods for the solving of the so called box linear complementarity problems (BLCPs) where the constraint matrices are restrictedly supposed to be of P ...Judice and Pires developed in recent years principal pivoting methods for the solving of the so called box linear complementarity problems (BLCPs) where the constraint matrices are restrictedly supposed to be of P matrices. This paper aims at presenting a new principal pivoting scheme for BLCPs where the constraint matrices are loosely supposed to be row sufficient.This scheme can be applied to the solving of convex quadratic programs subject to linear constraints and arbitrary upper and lower bound constraints on variables.展开更多
文摘Discovering cyclic generalized association rules from transaction datbases can reveal the relationship of differ-ent levels of the taxonomies and display cyclic variations over time.Information about such variations is great use of better identifying trends in associations and forecast-ing.Because cyclic rules are quite sensitive to a littlenoise,this paper uses the noise-ratio as the criterion of i-dentifing cydclic itemsets for dealing with the problem and utilizes the cycle-pruning technique to reduce the comput-ing time of the data mining process by exploiting the real-tionship between the cycle and generalized frequent item-sets.The paper gives the algorithm of mining cyclic gen-eralized itemsets(CGI).Experiment shows that the CGI algorithm can efficiently yield results.
文摘Judice and Pires developed in recent years principal pivoting methods for the solving of the so called box linear complementarity problems (BLCPs) where the constraint matrices are restrictedly supposed to be of P matrices. This paper aims at presenting a new principal pivoting scheme for BLCPs where the constraint matrices are loosely supposed to be row sufficient.This scheme can be applied to the solving of convex quadratic programs subject to linear constraints and arbitrary upper and lower bound constraints on variables.
