Symmetrization for Embedding Directed Graphs

November 06, 2018 Β· Declared Dead Β· πŸ› AAAI Conference on Artificial Intelligence

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Authors Jiankai Sun, Srinivasan Parthasarathy arXiv ID 1811.12164 Category cs.SI: Social & Info Networks Cross-listed cs.AI, cs.LG Citations 0 Venue AAAI Conference on Artificial Intelligence Last Checked 5 months ago
Abstract
Recently, one has seen a surge of interest in developing such methods including ones for learning such representations for (undirected) graphs (while preserving important properties). However, most of the work to date on embedding graphs has targeted undirected networks and very little has focused on the thorny issue of embedding directed networks. In this paper, we instead propose to solve the directed graph embedding problem via a two-stage approach: in the first stage, the graph is symmetrized in one of several possible ways, and in the second stage, the so-obtained symmetrized graph is embedded using any state-of-the-art (undirected) graph embedding algorithm. Note that it is not the objective of this paper to propose a new (undirected) graph embedding algorithm or discuss the strengths and weaknesses of existing ones; all we are saying is that whichever be the suitable graph embedding algorithm, it will fit in the above proposed symmetrization framework.
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