An Algorithm of Complement Mining Frequent Neighboring Class Set
In frequent neighboring class set mining, when generating candidate frequent itemset, present algorithms have some redundant candidate and repetitive computing, and so this paper proposes an algorithm of complementary mining frequent neighboring class set, which is suitable for mining any frequent neighboring class set This algorithm adopts double search strategies to generate candidate frequent neighboring class set in the mining course. One is using down-up search strategy to generate candidate, namely, it connects two k-frequent neighboring class sets to generate (k+l)-candidate frequent neighboring class set. The other is computing complement set of (k+I)-candidate to generate next candidate frequent neighboring class set. By the two ways, the algorithm may delete redundant candidate and repetitive computing. The algorithm creates digital database of neighboring class set via neighboring class weight, according to character of database, it also uses digit logical operation to computes support. The result of experiment indicates that the algorithm is faster and more efficient than present algorithms when mining frequent neighboring class set in large spatial data.
complementary mining complement set down-up search neighboring class weight spatial data mining
Ji-Ping ZENG Gang FANG
Chongqing Three Gorges University Chongqing 404000, P.R. China
国际会议
重庆
英文
99-102
2011-01-21（万方平台首次上网日期，不代表论文的发表时间）