Mining Complex Spatio-Temporal Sequence Patterns

Mining Complex Spatio-Temporal Sequence Patterns,Florian Verhein

Mining Complex Spatio-Temporal Sequence Patterns   (Citations: 2)
BibTex | RIS | RefWorks Download
Mining sequential movement patterns describing group behaviour in potentially streaming spatio-temporal data sets is a challenging problem. Movements are typically noisy and often overlap each other. This makes a set of simple patterns difficult to interpret and sequences diffi- cult to mine. Furthermore, group behaviour is complex. Objects in a group may behave similarly for a period of time (an interesting pattern sequence), then split up - either spatially, temporally or both; making a series of uninteresting movements before rejoining again. This behaviour must be captured in a single pattern for that group, rather than a number of unconnected pattern sequences. Secondly, it often occurs that individual ob- jects only move along segments of a path, perhaps be- tween intersections in a road or highway. However, the entire path is interesting when all such behaviours are taken together. Therefore, a pattern describing such behaviour should be found, rather than just a number of short sequences. This paper solves these challenges, among others, by mining sequences of Spatio-Temporal Association Rules. Theoretical results are exploited in order to develop an efficient algorithm, which is demon- strated to have linear run time in the number of inter- esting sequences discovered. A lattice for drill down and roll up exploratory analysis of the sequence patterns is proposed. Finally, verifiable and interesting patterns possessing the above characteristics are found in a real world animal tracking data set.
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
Sort by: