LINE:Large-scale Information Network Embedding

1.运用场景

????which is suitable for arbitrary types of information networks:undirected,directed,and/or weighted。

2.创新点

????which suits arbitrary types of information networks and easily scales to millions of nodes.It has a carefully designed objective function that preserves both the first-order and second-order proximities;
????propose an edge-sampling algorithm for optimizing the objective.The algorithm tackles the limitation of the classical stochastic gradient decent and improves the effectiveness and efficiency of the inference。

3.算法原理

3.1 网络框架

LINE:Large-scale Information Network Embedding

3.2 LINE

????LINE论文

4.算法理解

????同时考虑first-order proximity and second-order proximity。

LINE:Large-scale Information Network Embedding

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