Considering that massive uncertain radio frequency identification (RFID) data cannot be efficiently processed in application systems of traceability supply chains, key features of RFID applications were analyzed, and different smoothing windows were adjusted according to different rates of uncertain data. Different types of uncertain readings were obtained by employing different strategies, and the methods for efficiently and effectively processing various types of uncertain data were put forward. The methods distinguish between ghost, missing and incomplete data according to their appearing positions and their continuities in supply chains. The processing algorithms that are suitable to group and independent moving of objects were proposed based on the directed graph, which corresponds to moving paths of objects in logistics nodes. The results show that the proposed methods provide good cleaning effects, storage efficiencies, and query performances, and also efficiently support path-oriented queries of objects under different parameters.%针对可追踪供应链应用系统中大量非确定性RFID数据不能被有效处理的问题，通过分析RFID应用的关键特征，根据非确定性数据的比例来调整滑动窗口，采用不同策略处理不同类型的非确定性数据，提出可处理各种类型非确定性数据的清洗方法；根据对象在供应链中出现的位置及其连续性来区分多读、漏读和不完整数据，基于对象在物流节点中移动路径对应的有向图进一步提出可适应对象分组和独立移动的处理算法。研究结果表明：提出的方法具有良好的清洗效果、存储效率以及查询性能，在不同参数条件下能有效地支持对象路径查询。
展开▼
