TensorFlow implementation of paper LINE: Large-scale Information Network Embedding by Jian Tang, et al.

You can see my slide on GDG DevFest 2017 for more detail about LINE and TensorFlow. Notice: code shown in the slide are pseudocode, minibatch and negative sampling are omitted in the slide.

• Python 3.6
• TensorFlow 1.3.0
• Networkx
• NumPy

• Prepare a network using networkx. Write the graph to a file by nx.write_gpickle.
• Put the network file in data folder.
• Run line.py --graph_file graph.pkl to start training. graph.pkl is the name of your network file.
• Embedding will be stored in data/embedding_XXX-order.pkl. You can load it by pickle.load() in python.

• Tang, Jian, et al. "Line: Large-scale information network embedding." Proceedings of the 24th International Conference on World Wide Web. International World Wide Web Conferences Steering Committee, 2015.