CAJ | 학술논문

提出了一种层次二部图行为模式分析模型以及相应的挖掘算法,可获取潜在的时空周期行为模式,同时能克服以往算法的子集漏选问题.在此基础上,所设计的地点获取算法可以获取近似最小地点控制子集,尽早对少量地点进行监控.实验表明算法能全面地抽取周期地点子集,获取近似的最小地点控制子集,挖掘出常用地点以覆盖大部分周期行为个体.
제출료일충층차이부도행위모식분석모형이급상응적알굴산법,가획취잠재적시공주기행위모식,동시능극복이왕산법적자집루선문제.재차기출상,소설계적지점획취산법가이획취근사최소지점공제자집,진조대소량지점진행감공.실험표명산법능전면지추취주기지점자집,획취근사적최소지점공제자집,알굴출상용지점이복개대부분주기행위개체.
A hierarchical bipartite graph based model and a mining algorithm were presented to obtain the potential spa-tio-temporal periodic behavior, meanwhile avoided the subset omitting problem in previous schemes. Then the location analysis algorithm was designed to achieve the nearly minimum location dominating subset, it could monitor the small portion of the locations as early as possible. Finally, the experiments results show that the algorithms can find out the pe-riodic location set as well as obtain nearly minimum location dominating subset, so as to cover the major portion of ob-jectives using those popular locations.