Abstract
Discovering relationships between vertices in a secured information network is an important task in information network analysis. In HIN, meta-path, or a sequence of vertex types and edge types connecting two vertices. Path instance of a meta-path is path in HIN that satisfies the meta-path. The length of meta-path is the number of relations (edges) in this meta-path. Meaningful meta-path is a meta-path with at least one path instance. Recent works on meta-path discovery mainly focus on in-memory algorithms that fit in only one computer. In this chapter, we propose distributed algorithms to discover all shortest meaningful meta-paths between two vertices of a large HIN using Apache Spark. Shortest meaningful meta-path is a meaningful meta-path with shortest length. We employ a scalable implementation of the Distributed Breadth-First Search (D-BFS) algorithm as a baseline approach. Finding all possible shortest paths in a large HIN can be time consuming. Therefore, we propose a novel algorithm called shortest meaningful meta-path based search (S-MPS). S-MPS first searches all shortest meta-path candidates between vertices in the graph of the network schema of HIN. We conduct experiments on DBLP data set to prove the efficiency of our proposed S-MPS algorithm over D-BFS.
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This research is funded by Vietnam National University Ho Chi Minh City (VNU-HCMC) under the grant number DS2020-26-01.
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Do, P. (2022). Finding All Shortest Meaningful Meta-Paths Between Two Vertices of a Secured Large Heterogeneous Information Network Using Distributed Algorithm. In: Nedjah, N., Abd El-Latif, A.A., Gupta, B.B., Mourelle, L.M. (eds) Robotics and AI for Cybersecurity and Critical Infrastructure in Smart Cities. Studies in Computational Intelligence, vol 1030. Springer, Cham. https://doi.org/10.1007/978-3-030-96737-6_10
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