Sameera Kannangara
ABSTRACT
There are many real world applications that require to identify movement of users such as identifying movement corridors, most popular paths, and nearest neighbours. If one is not given trajectories mapping to movement of people but rather sporadic location data, such as location based social network data, finding movement related information becomes difficult. Rather than processing all points in a data set given a query, a clever approach is to construct a graph, based on user locations, and query this graph for all queries. One example is the shortest path graph. However the shortest path graph can be inefficient and ineffective analysing movement, as it calculates the graph considering all points in a data set. We propose the stepping stone graph, which calculates graph considering point pairs rather than all points, that focuses on local possible movement, making it both efficient and effective for location based social network related queries. We demonstrate its uses by applying it in the aforementioned domain and comparing with the shortest path graph. We also compare its properties to a range of other graphs.
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Index Terms
- Stepping stone graph for public movement analysis
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