Timestamps are often found to be dirty in various scenarios, e.g., in distributed systems with clock synchronization problems or unreliable RFID readers. Without cleaning the imprecise timestamps, temporal-related applications such as provenance analysis or pattern queries are not reliable. To evaluate the correctness of timestamps, temporal constraints could be employed, which declare the distance restrictions between timestamps. Guided by such constraints on timestamps, in this paper, we study a novel problem of repairing inconsistent timestamps that do not conform to the required temporal constraints. Following the same line of data repairing, the timestamp repairing problem is to minimally modify the timestamps towards satisfaction of temporal constraints. This problem is practically challenging, given the huge space of possible timestamps. We tackle the problem by identifying a concise set of promising candidates, where an optimal repair solution can always be found. Repair algorithms with efficient pruning are then devised over the identified candidates. Approximate solutions are also presented including simple heuristic and linear programming (LP) relaxation. Experiments on real datasets demonstrate the superiority of our proposal compared to the state-of-the-art approaches.

在各种情况下，例如在存在时钟同步问题的分布式系统或不可靠的RFID读取器中，经常发现时间戳很脏。如果不清除不精确的时间戳，则与时间相关的应用程序（如出处分析或模式查询）将不可靠。评估时间戳，时间约束的正确性可以使用，它声明了时间戳之间的距离限制。在这种对时间戳的约束的指导下，本文研究了一种新的问题，即修复不一致的时间戳，这些时间戳不符合所需的时间约束。遵循相同的数据修复方法，时间戳修复问题是将时间戳最小化修改以满足时间约束。考虑到可能的时间戳记的巨大空间，这个问题实际上具有挑战性。我们通过确定一组简明的有前途的候选人来解决该问题，在其中始终可以找到最佳的维修解决方案。然后，针对识别出的候选对象设计出具有有效修剪功能的修复算法。还提出了近似解决方案，包括简单的启发式和线性规划（LP）松弛。