计算机科学 ›› 2018, Vol. 45 ›› Issue (3): 223-230.doi: 10.11896/j.issn.1002-137X.2018.03.035
张永梅,郭莎,季艳,马礼,张睿
ZHANG Yong-mei, GUO Sha, JI Yan, MA Li and ZHANG Rui
摘要: 大多数数据库都不能有效地处理数据的时间维度,时空同现模式挖掘有利于提取隐含在时空数据集中有价值的信息,目前已经成为研究热点。针对现有同现模式发现方法挖掘效率较低的问题,采用双层网络对时空数据进行初始化建模,针对传统方法在进行时空兴趣度计算时未考虑对象类型存在有效周期的问题,改进了现有兴趣度计算方法,引入了权重特征值,并提出了基于网络的时空同现模式挖掘算法。实验表明,在使用不同数据量的测试集中挖掘同现模式集时,新算法的运行效率优于不对数据集进行建模的方法以及仅对实例层进行建模的方法。
[1] CAI J N,LIU Q L,XU F,et al.An Adaptive Method Mining Hierarchical Spatio Co-location Patterns[J].Acta Geodaetica et Cartographica Sinica,2016,5(4):474-485.(in Chinese) 蔡建南,刘启亮,徐枫,等.多层次空间同位模式自适应挖掘方法[J].测绘学报,2016,5(4):474-485. [2] AKBARI M,SAMADZADEGAN F,ROBERT W.A generic regional spatial-temporal co-occurrence pattern mining model:a case study for air pollution[J].Journal of Geographical Systems,2015,7(3):249-274. [3] ZHAO X J,SUN Z X,YUAN Y.An Efficient Association Rule Mining Algorithm Based on Prejudging and Screening[J].Journal of Electronics & Information Technology,2016,8(7):1654-1659.(in Chinese) 赵学健,孙知信,袁源.基于预判筛选的高效关联规则挖掘算法[J].电子与信息学报,2016,8(7):1654-1659. [4] MAOLEGI M A,ARKOK B.An improved Apriori algorithm for association rules[J].International Journal on Natural Language Computing,2014,3(1):21-29. [5] TANK D M.Improved algorithm for mining association rules[J].International Journal of Information Technology and Computer Science,2014,6(7):15-23. [6] GE L,JI X S,JIANG T.Discovery of network information content security incidents based on association rules and its implementation in Map-Reduce[J].Journal of Electronics & Information Technology,2014,6(8):1831-1837.(in Chinese) 葛琳,季新生,江涛.基于关联规则的网络信息内容安全事件发现及其Map-Reduce的实现[J].电子与信息学报,2014,6(8):1831-1837. [7] YOO J S,SHEKHAR S.A Joinless Approach for Mining Spatial Colocation Patterns[J].IEEE Transactions on Knowledge and Data Engineering,2006,8(10):1323-1337. [8] HUANG Y,ZHANG L,ZHANG P.A framework for miningsequential patterns from spatio-temporal event databases[J].IEEE Transactions on Knowledge and Data Engineering,2008,20(4):433-448. [9] CELIK M.Partial spatio-temporal co-occurrence pattern mining[J].Knowledge and Information Systems,2015,4(1):27-49. [10] PILLAI K G,ANGRYK R A,BANDA J M,et al.Spatiotemporal co-occurrence rules[C]∥New Trends in Databases and Information Systems:17th East European Conference on Advances in Databases and Information Systems.Berlin,German:Springer International Publishing,2014:27-35. [11] TIAN J,WANG Y H,YAN F,et al.A New Method for Co-location Patterns Between Network Spatial Phenomena[J].Wuhan University(Geomatics and Information Science),2015,0(5):652-660.(in Chinese) 田晶,王一恒,颜芬,等.一种网络空间现象同位模式挖掘的新方法[J].武汉大学学报(信息科学版),2015,0(5):652-660. [12] WANG Z Q,PENG X G,GU C H.Mining At Most Top-K% Mixed-drove Spatio-temporal Co-occurrence Patterns[C]∥Proceedings of 2013 9th Asian Control Conference (ASCC).Piscata-way,NJ:IEEE Press,2013:1-5. [13] BARUA S,SANDER J.Mining Statistically Significant Co-location and Segregation Patterns[J].IEEE Transactions on Know-ledge and Data Engineering,2014,6(5):1185-1199. [14] QIAN F,CHIEW K,HE Q M,et al.Mining Regional Co-location Patterns with kNNG[J].Journal of Intelligent Information Systems,2014,2(3):485-505. [15] AKBARI M,SAMADZADEGAN F.Identification of air pollution patterns using a modified fuzzy co-occurrence pattern mi-ning method[J].International Journal of Environmental Science and Technology,2015,2(11):3551-3562. [16] YUAN J,ZHENG Y,XIE X,et al.Driving with knowledge from the physical world[C]∥Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD’11).New York,USA:ACM,2011:316-324. [17] YUAN J,ZHENG Y,ZHANG C Y,et al.T-drive:driving directions based on taxi trajectories[C]∥Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS’10).New York,USA:ACM,2010:99-108. |
No related articles found! |
|