文档介绍：PRESS: A Novel Framework of pression in worksRenchu Song, Weiwei Sun, Fudan UniversityBaihua Zheng, Singapore Management UniversityYu Zheng, Microsoft Research, Beijing2Background?Big Data–Huge volume of spatial trajectories cause heavy burden to data storage and data process–Trajectories contain redundant parts that contribute very limited to spatial and temporal informationSolution: pressionPRESS: Paralleled work-based pressionMap matcherTrajectoryre-pressorSpatial pathTemporal pressedspatial pressedtemporal sequenceMap trajectoryGPS trajectoryPRESSLocation-based servicesPRESS (cont’d)?Key highlights–Separate the spatial path from the temporal information when presenting a trajectory–Propose a lossless pression algorithm HSC –Propose an error-bounded pression algorithm BTC–Support multiple popular location-based services without fully pressing the trajectories4Trajectory Representation?Traditional representation–(x1,y1,t1), (x2, y2,t1) …?Spatial path–The sequence of road segments passed by a trajectory?Temporal sequence–The sequence of (di,ti) vectors?di refers to the distance travelled from the start of the trajectory until time stamp tiHSC: pression?Hybrid pression (HSC) is lossless, and it consists of two stages6STAGE 1Shortest pressionSTAGE 2Frequent Sub-pressionoInput: spatial path (consecutive edge sequence)oOutput: non-consecutive edge sequenceoInput: non-consecutive edge sequenceoOutput binary codeHSC Stage 1: Shortest pression?Observation: given a source s and a destination d, most of the time we take the shortest path between sand d if all the edges roughly share the similar traffic condition?Given an edge sequence–If the sequence refers to the shortest path from to , we will replace the sequence with–7HSC Stage 2: Frequent Sub-pression?Observation: certain road segments are much more popular than others?Basic idea: We can treat the sequence of edges as a string, and can employ suitable coding techniques to use fewer bits to represent mon sub-s