CAJ | 학술논문

在移动商务服务方面，通过特定周期内的客户周期性移动的趋势可以有效地对移动系统资源进行分配，并且提供个性化的基于位置的服务（LBS）。本文对最有前途的周期运动模式进行挖掘，整个过程根据图映射来进行，并提出几种取样方法以提高挖掘效率。首先，从时间区间随机选取一条运动路径作为样本；然后，创建一个独特的路径图结构以储存来自样本的运动路径；最后，应用图遍历算法来鉴定哪些运动模式最有前途。实验结果表明该采样方法在定期最有前途的周期运动模式中执行效率高效、可伸缩性优越。
재이동상무복무방면，통과특정주기내적객호주기성이동적추세가이유효지대이동계통자원진행분배，병차제공개성화적기우위치적복무（LBS）。본문대최유전도적주기운동모식진행알굴，정개과정근거도영사래진행，병제출궤충취양방법이제고알굴효솔。수선，종시간구간수궤선취일조운동로경작위양본；연후，창건일개독특적로경도결구이저존래자양본적운동로경；최후，응용도편력산법래감정나사운동모식최유전도。실험결과표명해채양방법재정기최유전도적주기운동모식중집행효솔고효、가신축성우월。
Mobile commerce service cyclical trend of moving by the customers within a specific period can be effectively mobile system resources allocation, and providing personalized location-based services (LBS). Movement patterns of the most promising cycles excavation, the whole process is carried out according to the graph maps, and put forward several sampling methods to improve the efficiency of mining. First of all, from the time interval randomly select a motion path as a sample; then create a unique path graph structure to store the movement path from the sample; Finally, the application graph traversal algorithm which movement patterns to identify the most promising. Experimental results show that the sampling method in the periodic cycle of the most promising motion mode to perform efficient efficiency, scalability superior.