Abstract
We apply techniques that originate in the analysis of market basket data sets to the study of frequent trajectories in graphs. Trajectories are defined as simple paths through a directed graph, and we put forth some definitions and observations about the calculation of supports of paths in this context. A simple algorithm for calculating path supports is introduced and analyzed, but we explore an algorithm which takes advantage of traditional frequent item set mining techniques, as well as constraints placed on supports by the graph structure, for optimizing the calculation of relevant supports. To this end, the notion of the path tree is introduced, as well as an algorithm for producing such path trees.
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Lo, H.Z., Simovici, D.A., Ding, W. (2012). Several Remarks on Mining Frequent Trajectories in Graphs. In: Jiang, H., Ding, W., Ali, M., Wu, X. (eds) Advanced Research in Applied Artificial Intelligence. IEA/AIE 2012. Lecture Notes in Computer Science(), vol 7345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31087-4_9
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DOI: https://doi.org/10.1007/978-3-642-31087-4_9
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