首页> 外文会议>Algorithms - ESA 2008 >Detecting Regular Visit Patterns
【24h】

Detecting Regular Visit Patterns

机译:检测常规访问模式

获取原文

摘要

We are given a trajectory T and an area A. T might intersect A several times, and our aim is to detect whether T visits A with some regularity, e.g. what is the longest time span that a GPS-GSM equipped elephant visited a specific lake on a daily (weekly or yearly) basis, where the elephant has to visit the lake most of the days (weeks or years), but not necessarily on every day (week or year). During the modelling of such applications, we encounter an elementary problem on bitstrings, that we call LDS (LongestDenseSubstring). The bits of the bitstring correspond to a sequence of regular time points, in which a bit is set to 1 iff the trajectory T intersects the area A at the corresponding time point. For the LDS problem, we are given a string s as input and want to output a longest substring of s, such that the ratio of l's in the substring is at least a certain threshold. In our model, LDS is a core problem for many applications that aim at detecting regularity of T intersecting A. We propose an optimal algorithm to solve LDS, and also for related problems that are closer to applications, we provide efficient algorithms for detecting regularity.
机译:我们给定了一条轨迹T和一个面积A.T可能与A相交多次,我们的目标是检测T是否以某种规律性访问A,例如配备GPS-GSM的大象每天(每周或每年)访问特定湖泊的最长时间是多长,大象必须在大部分时间(几周或几年)访问该湖泊,但不一定每次都要访问天(周或年)。在此类应用程序的建模过程中,我们在位串上遇到一个基本问题,我们称之为LDS(LongestDenseSubstring)。位串的位对应于规则时间点的序列,其中,如果轨迹T在相应的时间点与区域A相交,则将位设置为1。对于LDS问题,我们给定字符串s作为输入,并希望输出s的最长子字符串,以使l在子字符串中的比率至少为某个阈值。在我们的模型中,LDS是许多旨在检测与T相交的T的规律性的应用程序的核心问题。我们提出了一种解决LDS的最佳算法,并且针对更接近应用程序的相关问题,我们提供了检测规律性的有效算法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号