会议专题

An Algorithm of Fast Duplex Mining Frequent Neighboring Class Set

In the course of mining frequent neighboring class set, present algorithms have some redundant candidate and repetitive computing, which are only able to efficiently extract short frequent neighboring class set, and so this paper proposes an algorithm of fast duplex mining frequent neighboring class set, which is suitable for mining any frequent neighboring class set This algorithm adopts two methods to generate candidate frequent neighboring class set in the mining course. One is using top-down search strategy to generate candidate by numerical index, the other is using anti-code of front this candidate to generate next candidate frequent neighboring class set. The course of top-down search strategy used by the algorithm isnt different from traditional top-down search strategy, which uses numerical index to generates Ac-subset of (k+)-non frequent neighboring class set. By the two methods, 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.

numerical index anti-code top-down search neighboring class weight spatial data mining

Gang FANG Fu-Ming LIU Jiang XIONG Xiang-Lin DU Cheng-sheng TU

College of Mathematics and Computer Science Chongqing Three Gorges University Chongqing 404000, P.R. China

国际会议

2011 3rd International Conference on Computer and Automation Engineering(ICCAE 2011)(2011年第三届IEEE计算机与自动化工程国际会议)

重庆

英文

136-139

2011-01-21(万方平台首次上网日期,不代表论文的发表时间)