{"id":23406,"date":"2021-01-21T13:18:10","date_gmt":"2021-01-21T05:18:10","guid":{"rendered":"https:\/\/swarma.org\/?p=23406"},"modified":"2021-01-21T13:18:10","modified_gmt":"2021-01-21T05:18:10","slug":"%e6%b7%b1%e5%ba%a6%e5%9b%be%e7%94%9f%e6%88%90%e6%a8%a1%e5%9e%8b%e7%bb%bc%e8%bf%b0%ef%bc%9a5%e7%b1%bb%e6%a8%a1%e5%9e%8b%e5%8f%8a%e5%89%8d%e6%99%af%ef%bc%88%e9%99%84pdf%e4%b8%8b%e8%bd%bd%ef%bc%89","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=23406","title":{"rendered":"\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b\u7efc\u8ff0\uff1a5\u7c7b\u6a21\u578b\u53ca\u524d\u666f\uff08\u9644PDF\u4e0b\u8f7d\uff09"},"content":{"rendered":"
<\/p>\n

\u5bfc\u8bed<\/p>\n

\u5728\u8fc7\u53bb\u7684\u51e0\u5e74\u4e2d\uff0c\u6df1\u5ea6\u751f\u6210\u6a21\u578b\u5728\u56fe\u50cf\u3001\u8bed\u97f3\u548c\u81ea\u7136\u8bed\u8a00\u5904\u7406\u7b49\u9886\u57df\u5df2\u7ecf\u53d6\u5f97\u4e86\u5de8\u5927\u7684\u6210\u529f\u3002\u5f97\u76ca\u4e8e\u57fa\u4e8e\u56fe\u7684\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u7684\u8fdb\u6b65\uff0c\u56fe\u751f\u6210\u6a21\u578b\u6709\u4e86\u53d1\u73b0\u65b0\u9896\u7684\u5206\u5b50\u7ed3\u6784\u3001\u5efa\u6a21\u793e\u4ea4\u7f51\u7edc\u7b49\u5728\u56fe\u4e0a\u7684\u65b0\u5e94\u7528\u3002\u8fd1\u65e5arXiv\u7684\u4e00\u7bc7\u7efc\u8ff0\u6587\u7ae0\u5bf9\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u56fe\u751f\u6210\u6a21\u578b\u8fdb\u884c\u4e86\u5168\u9762\u7684\u8c03\u67e5\uff0c\u5c06\u73b0\u6709\u6a21\u578b\u5212\u5206\u4e3a\u4e94\u5927\u7c7b\uff0c\u5e76\u5206\u522b\u8fdb\u884c\u4e86\u8be6\u5c3d\u7684\u63cf\u8ff0\uff0c\u672c\u6587\u662f\u5bf9\u8be5\u6587\u7ae0\u5185\u5bb9\u7684\u6574\u4f53\u4ecb\u7ecd\u3002<\/p>\n


\u626b\u7801\u83b7\u53d6\u8bba\u6587PDF\u9648\u660a | \u4f5c\u8005
\u9093\u4e00\u96ea | \u7f16\u8f91
 <\/p>\n

\u56fe\u751f\u6210\u6a21\u578b\u662f\u590d\u6742\u7f51\u7edc\u9886\u57df\u7814\u7a76\u7684\u7ecf\u5178\u95ee\u9898\uff0cEndos-Renyi\uff08ER\uff09\u6a21\u578b\u3001Barabasi-Albert\uff08BA\uff09\u6a21\u578b\u7b49\u7ecf\u5178\u56fe\u751f\u6210\u6a21\u578b\u53ef\u4ee5\u5f88\u597d\u5730\u63ed\u793a\u771f\u5b9e\u56fe\u7684\u6027\u8d28\uff0c\u4f46\u8fd9\u7c7b\u6a21\u578b\u4ecd\u5b58\u5728\u7740\u7ed3\u6784\u56fa\u5b9a\u3001\u8868\u793a\u80fd\u529b\u6709\u9650\u7b49\u95ee\u9898\u3002\u8fd1\u5e74\u6765\u968f\u7740\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u5c24\u5176\u662f\u56fe\u8868\u793a\u5b66\u4e60\u7684\u53d1\u5c55\uff0c\u8d8a\u6765\u8d8a\u591a\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u56fe\u751f\u6210\u6a21\u578b\u88ab\u63d0\u51fa\u3002
\u6700\u8fd1\u6302\u4e0aarXiv\u7684\u7efc\u8ff0\u6587\u7ae0\u300aDeep Graph Generators: A Survey\u300b\u5c06\u8fd9\u4e9b\u6a21\u578b\u5212\u5206\u4e3a\u4e94\u5927\u7c7b\uff0c\u5206\u522b\u662f\uff1a \u81ea\u56de\u5f52\uff08autoregressive\uff09\u6a21\u578b\u3001\u57fa\u4e8e\u81ea\u7f16\u7801\u5668\uff08autoencoder-based\uff09\u7684\u6a21\u578b\u3001\u57fa\u4e8e\u5f3a\u5316\u5b66\u4e60\uff08RL-based\uff09\u7684\u6a21\u578b\u3001\u751f\u6210\u5bf9\u6297\u7f51\u7edc\uff08GAN\uff09\u6a21\u578b\uff0c\u4ee5\u53ca\u57fa\u4e8e\u6d41\uff08flow-based\uff09\u7684\u6a21\u578b\u3002\u5e76\u9488\u5bf9\u6bcf\u4e2a\u7c7b\u522b\u4e2d\u7684\u91cd\u8981\u6a21\u578b\u63d0\u4f9b\u4e86\u8be6\u7ec6\u7684\u63cf\u8ff0\u3002 \u8bba\u6587\u9898\u76ee\uff1aDeep Graph Generators: A Survey\u8bba\u6587\u5730\u5740\uff1ahttps:\/\/arxiv.org\/abs\/2012.15544v1<\/p>\n


1. \u6a21\u578b\u76ee\u6807\u5b9a\u4e49<\/p>\n

\u7ed9\u5b9a\u4e00\u4e2a\u6ee1\u8db3\u6f5c\u5728\u6570\u636e\u5206\u5e03\u7684\u56fe\u6570\u636e\u96c6\uff0c\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b\u7684\u76ee\u7684\u662f\u5229\u7528\u6df1\u5ea6\u795e\u7ecf\u7f51\u7edc\u4ece\u6570\u636e\u96c6\u4e2d\u4f30\u8ba1\u5176\u6ee1\u8db3\u7684\u5206\u5e03\uff0c\u7136\u540e\u4ece\u4f30\u8ba1\u7684\u5206\u5e03\u4e2d\u83b7\u53d6\u65b0\u7684\u56fe\u6837\u672c\u3002\u4e0e\u4f20\u7edf\u56fe\u751f\u6210\u6a21\u578b\u4e0d\u540c\uff0c\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b\u4e0d\u9700\u8981\u5bf9\u5206\u5e03\u8fdb\u884c\u663e\u5f0f\u7684\u5efa\u6a21\u3002<\/p>\n

2. \u81ea\u56de\u5f52\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b<\/p>\n



\u81ea\u56de\u5f52\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b\u9010\u6b65\u987a\u5e8f\u5730\u751f\u6210\u5b8c\u6574\u7684\u56fe\u7ed3\u6784\uff0c\u6bcf\u4e2a\u65f6\u95f4\u6b65\u7684\u9884\u6d4b\u7ed3\u679c\u90fd\u4f1a\u53d7\u5230\u5df2\u6709\u56fe\u7ed3\u6784\u7684\u5f71\u54cd\u3002\u8fd9\u7c7b\u6a21\u578b\u8fd8\u53ef\u4ee5\u8fdb\u4e00\u6b65\u5212\u5206\u4e3a\u6709\u5faa\u73af\u5355\u5143\u548c\u65e0\u5faa\u73af\u5355\u5143\u4e24\u7c7b\uff0c\u524d\u8005\u4f7f\u7528\u5faa\u73af\u5355\u5143\u6355\u83b7\u5386\u53f2\u4fe1\u606f\uff0c\u800c\u540e\u8005\u5219\u76f4\u63a5\u4f9d\u7167\u6700\u8fd1\u7684\u751f\u6210\u7b56\u7565\u505a\u51fa\u51b3\u7b56\u3002<\/p>\n

\u6709\u5faa\u73af\u5355\u5143\u7684\u81ea\u56de\u5f52\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b\u4f7f\u7528RNN\u6355\u83b7\u5f53\u524d\u65f6\u523b\u4e4b\u524d\u6240\u6709\u65f6\u523b\u7684\u4fe1\u606f\u3002\u4ee3\u8868\u5de5\u4f5c\u6709Jiaxuan You[1]\u7b49\u4eba\u63d0\u51fa\u7684GraphRNN\u6a21\u578b\uff08\u5982\u56fe1\uff09\u6240\u793a\u3002\u8be5\u6a21\u578b\u5c06\u4e0d\u540c\u8282\u70b9\u987a\u5e8f\u4e0b\u7684\u56fe\u8868\u793a\u4e3a\u5e8f\u5217\uff0c\u5e76\u5728\u8fd9\u4e9b\u5e8f\u5217\u4e0a\u6784\u5efa\u4e00\u4e2a\u81ea\u56de\u5f52\u7684\u751f\u6210\u6a21\u578b\u3002
\u56fe1 GraphRNN\u6a21\u578b\u7684\u56fe\u751f\u6210\u8fc7\u7a0b\uff0c\u7eff\u8272\u7bad\u5934\u8868\u793a\u8fde\u8868\u5c42\u9762\u7684RNN\u3001\u84dd\u8272\u7bad\u5934\u8868\u793a\u8282\u70b9\u5c42\u9762\u7684RNN<\/p>\n

\u4e0e\u6709\u5faa\u73af\u5355\u5143\u7684\u56fe\u751f\u6210\u6a21\u578b\u4e0d\u540c\uff0c\u65e0\u5faa\u73af\u5355\u5143\u7684\u56fe\u795e\u7ecf\u7f51\u7edc\u53ea\u5173\u6ce8\u6700\u8fd1\u65f6\u523b\u7684\u4fe1\u606f\u3002\u4ee5 GRANs\u6a21\u578b\uff08Graph Recurrent Attention Networks\uff09[2]\u4e3a\u4f8b\uff0c\u8be5\u6a21\u578b\u5c06\u56fe\u751f\u6210\u8fc7\u7a0b\u5212\u5206\u6210\u591a\u4e2a\u65f6\u95f4\u5757\uff08\u5982\u56fe2\uff09\uff0c\u91c7\u7528\u6ce8\u610f\u529b\u673a\u5236\u8ba1\u7b97\u65b0\u52a0\u5165\u56fe\u7ed3\u6784\u7684\u8282\u70b9\u4e0e\u5df2\u5b58\u5728\u8282\u70b9\u95f4\u4ea7\u751f\u8fde\u8fb9\u7684\u6982\u7387\u3002
\u56fe2 GRANs\u6a21\u578b \u76f8\u540c\u989c\u8272\u7684\u8282\u70b9\u5c5e\u4e8e\u540c\u4e00\u65f6\u95f4\u5757 (\u5757\u5927\u5c0f\u4e3a2)<\/p>\n

3. \u57fa\u4e8e\u81ea\u7f16\u7801\u5668\u7684\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b<\/p>\n



\u8be5\u7c7b\u6a21\u578b\u901a\u5e38\u4f7f\u7528\u56fe\u795e\u7ecf\u7f51\u7edc\u6216\u5176\u53d8\u4f53\u5c06\u8bad\u7ec3\u56fe\u7f16\u7801\u81f3\u9690\u7a7a\u95f4\uff0c\u800c\u540e\u518d\u89e3\u7801\u751f\u6210\u56fe\u3002GraphVAE[3]\u5728\u8be5\u7c7b\u6a21\u578b\u4e2d\u5341\u5206\u5177\u6709\u4ee3\u8868\u6027\u3002\u5982\u56fe3\u6240\u793a\uff0c\u8be5\u6a21\u578b\u4f7f\u7528\u4e34\u754c\u77e9\u9635\u3001\u8fde\u8fb9\u5c5e\u6027\u5f20\u91cf\u53ca\u8282\u70b9\u5c5e\u6027\u77e9\u9635\u8868\u793a\u5bf9\u56fe\u8fdb\u884c\u8868\u793a\u3002\u91c7\u7528encoder-decoder\u7ed3\u6784\u8fdb\u884c\u5b66\u4e60\u30022020\u5e74\u7684\u6700\u65b0\u5de5\u4f5cNED-VAE[4]\u5219\u4f7f\u7528\u4e09\u4e2a\u7f16\u7801\u5668\u4ee5\u53ca\u4e24\u4e2a\u89e3\u7801\u5668\u5c06\u8fde\u8fb9\u5c5e\u6027\u548c\u8282\u70b9\u5c5e\u6027\u7684\u5b66\u4e60\u90e8\u5206\u5206\u79bb\uff08\u56fe4\uff09\u3002<\/p>\n

\u56fe3 GraphVAE\u6a21\u578b A\u4e3a\u90bb\u63a5\u77e9\u9635\u3001E\u4e3a\u8fde\u8fb9\u5c5e\u6027\u5f20\u91cf\u3001F\u4e3a\u8282\u70b9\u5c5e\u6027\u77e9\u9635
 \u56fe4 NED-VAE\u6a21\u578b\u7684\u7ed3\u6784 \u5305\u542b\u4e09\u4e2a\u5b50\u7f16\u7801\u5668\u4e0e\u4e24\u4e2a\u5b50\u89e3\u7801\u5668<\/p>\n


4. \u751f\u6210\u5bf9\u6297\u7f51\u7edc\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b<\/p>\n

\u8be5\u7c7b\u6a21\u578b\u5c06\u56fe\u7ed3\u6784\u4e0e\u751f\u6210\u5bf9\u6297\u7f51\u7edc\uff08GAN\uff09\u76f8\u7ed3\u5408\u3002\u4ee5MolGAN\u4e3a\u4f8b[5]\uff0c\u4ece\u5148\u9a8c\u6837\u672c\u4e2d\u91c7\u6837\u5f97\u5230\u5411\u91cfz\u5e76\u4f20\u9012\u7ed9\u901a\u8fc7MLP\u5b9e\u73b0\u7684\u751f\u6210\u5668\uff0c\u751f\u6210\u5668\u8f93\u51fa\u56fe\u8868\u793a\u3002\u4ee5\u56fe\u795e\u7ecf\u7f51\u7edc\u5b9e\u73b0\u7684\u5224\u522b\u5668\u5bf9\u56fe\u6765\u81ea\u4e8e\u751f\u6210\u5668\u8fd8\u662f\u6570\u636e\u96c6\u8fdb\u884c\u5206\u7c7b\u3002reward\u7f51\u7edc\u5219\u5229\u7528\u5916\u90e8\u8f6f\u4ef6\u63d0\u4f9b\u7684\u7279\u5b9a\u7ed3\u6784\u5bf9\u751f\u6210\u5668\u8fdb\u884c\u5956\u52b1\u3002
\u56fe5 MolGAN\u6a21\u578b\u793a\u610f\u56fe \u751f\u6210\u5668\u8d1f\u8d23\u751f\u6210\u4e0e\u56fe\u6570\u636e\u96c6\u4e2d\u7684\u771f\u5b9e\u56fe\u76f8\u4f3c\u7684\u56fe\uff0c\u5224\u522b\u5668\u8d1f\u8d23\u5224\u522b\u56fe\u662f\u5426\u4e3a\u6570\u636e\u96c6\u4e2d\u7684\u771f\u5b9e\u56fe<\/p>\n


5. \u603b\u7ed3<\/p>\n



\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b\u5c06\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u5c24\u5176\u662f\u56fe\u8868\u793a\u5b66\u4e60\u4e0e\u4f20\u7edf\u56fe\u751f\u6210\u6a21\u578b\u76f8\u7ed3\u5408\uff0c\u5728\u5206\u5b50\u7ed3\u6784\u53d1\u73b0\u3001\u5efa\u7acb\u77e5\u8bc6\u56fe\u8c31\u3001\u5efa\u6a21\u7269\u7406\u3001\u793e\u4f1a\u548c\u751f\u7269\u7f51\u7edc\u7b49\u9886\u57df\u6709\u4e86\u5e7f\u6cdb\u7684\u5e94\u7528\u3002\u5e76\u53ef\u80fd\u5728\u57fa\u4e8e\u8bed\u8a00\u7684\uff08language-based\uff09\u56fe\u751f\u6210\u95ee\u9898\u4ee5\u53ca\u573a\u666f\uff08sence\uff09\u56fe\u751f\u6210\u7b49\u9886\u57df\u53d1\u6325\u5176\u5de8\u5927\u4f5c\u7528\u3002\u672c\u7bc7\u7efc\u8ff0\u5c06\u4e3b\u8981\u7684\u6df1\u5ea6\u56fe\u751f\u6210\u6a21\u578b\u5206\u4e3a\u4e94\u5927\u7c7b\u8fdb\u884c\u4e86\u8be6\u7ec6\u7684\u4ecb\u7ecd\uff0c\u53ef\u4ee5\u4f7f\u8bfb\u8005\u83b7\u5f97\u5bf9\u8be5\u9886\u57df\u7684\u5168\u9762\u4e86\u89e3\u3002\u9664\u4ee5\u4e0a\u63d0\u5230\u7684\u4e09\u7c7b\u6a21\u578b\u5916\uff0c\u57fa\u4e8e\u5f3a\u5316\u5b66\u4e60\uff08RL-based\uff09\u4e0e\u57fa\u4e8e\u6d41\uff08flow-based\uff09\u7684\u6a21\u578b\u4e5f\u5728\u6587\u7ae0\u4e2d\u6709\u8be6\u7ec6\u7684\u4ecb\u7ecd\uff0c\u6b22\u8fce\u4e0b\u8f7d\u539f\u6587\u8fdb\u4e00\u6b65\u4e86\u89e3\u3002
\u53c2\u8003\u6587\u732e[1] You J, Ying R, Ren X, et al. Graphrnn: Generating realistic graphs with deep auto-regressive models[J]. arXiv preprint arXiv:1802.08773, 2018.[2] Liao R, Li Y, Song Y, et al. Efficient graph generation with graph recurrent attention networks[C]\/\/Advances in Neural Information Processing Systems. 2019: 4255-4265.[3] Simonovsky M, Komodakis N. Graphvae: Towards generation of small graphs using variational autoencoders[C]\/\/International Conference on Artificial Neural Networks. Springer, Cham, 2018: 412-422.[4] Guo X, Zhao L, Qin Z, et al. Node-Edge Co-disentangled Representation Learning for Attributed Graph Generation[C]\/\/International Conference on Knowledge Discovery and Data Mining (SIGKDD). 2020.[5] De Cao N, Kipf T. MolGAN: An implicit generative model for small molecular graphs[J]. arXiv preprint arXiv:1805.11973, 2018.<\/p>\n

\u590d\u6742\u79d1\u5b66\u6700\u65b0\u8bba\u6587


\u96c6\u667a\u6591\u56fe\u9876\u520a\u8bba\u6587\u901f\u9012\u680f\u76ee\u4e0a\u7ebf\u4ee5\u6765\uff0c\u6301\u7eed\u6536\u5f55\u6765\u81eaNature\u3001Science\u7b49\u9876\u520a\u7684\u6700\u65b0\u8bba\u6587\uff0c\u8ffd\u8e2a\u590d\u6742\u7cfb\u7edf\u3001\u7f51\u7edc\u79d1\u5b66\u3001\u8ba1\u7b97\u793e\u4f1a\u79d1\u5b66\u7b49\u9886\u57df\u7684\u524d\u6cbf\u8fdb\u5c55\u3002\u73b0\u5728\u6b63\u5f0f\u63a8\u51fa\u8ba2\u9605\u529f\u80fd\uff0c\u6bcf\u5468\u901a\u8fc7\u5fae\u4fe1\u670d\u52a1\u53f7\u300c\u96c6\u667a\u6591\u56fe\u300d\u63a8\u9001\u8bba\u6587\u4fe1\u606f\u3002\u626b\u63cf\u4e0b\u65b9\u4e8c\u7ef4\u7801\u5373\u53ef\u4e00\u952e\u8ba2\u9605\uff1a<\/p>\n

<\/div>\n

\u63a8\u8350\u9605\u8bfb<\/p>\n

\u4f7f\u7528Chung-Lu\u968f\u673a\u56fe\u6a21\u578b\u751f\u6210\u5927\u89c4\u6a21\u65e0\u6807\u5ea6\u7f51\u7edc | \u7f51\u7edc\u79d1\u5b66\u8bba\u6587\u901f\u901220\u7bc7<\/a>\u589e\u957f\u56fe\u7684\u751f\u6210\u56fe\u5377\u79ef\u7f51\u7edc | \u7f51\u7edc\u79d1\u5b66\u8bba\u6587\u901f\u901215\u7bc7<\/a>\u56fe\u7f51\u7edc\u5165\u95e8\u8def\u5f84\uff1a\u4ece\u7f51\u7edc\u79d1\u5b66\u89c6\u89d2\u51fa\u53d1\uff0c\u4e0a\u624b\u6df1\u5ea6\u5b66\u4e60\u524d\u6cbf\u6280\u672f<\/a>
\u52a0\u5165\u96c6\u667a\uff0c\u4e00\u8d77\u590d\u6742\uff01<\/a><\/p>\n

\u70b9\u51fb\u201c\u9605\u8bfb\u539f\u6587\u201d\uff0c\u8ffd\u8e2a\u590d\u6742\u79d1\u5b66\u9876\u520a\u8bba\u6587 <\/div>\n","protected":false},"excerpt":{"rendered":"

\u5bfc\u8bed \u5728\u8fc7\u53bb\u7684\u51e0\u5e74\u4e2d\uff0c\u6df1\u5ea6\u751f\u6210\u6a21\u578b\u5728\u56fe\u50cf\u3001\u8bed\u97f3\u548c\u81ea\u7136\u8bed\u8a00\u5904\u7406\u7b49\u9886\u57df\u5df2\u7ecf\u53d6\u5f97\u4e86\u5de8\u5927\u7684\u6210\u529f\u3002\u5f97\u76ca\u4e8e\u57fa\u4e8e\u56fe\u7684\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\u7684\u8fdb\u6b65\uff0c\u56fe\u751f\u6210\u6a21\u578b\u6709\u4e86\u53d1\u73b0\u65b0\u9896\u7684\u5206\u5b50\u7ed3\u6784\u3001\u5efa\u6a21\u793e\u4ea4\u7f51\u7edc\u7b49\u5728\u56fe\u4e0a\u7684\u65b0\u5e94\u7528\u3002\u8fd1\u65e5arXiv\u7684\u4e00\u7bc7\u7efc\u8ff0\u6587\u7ae0\u5bf9\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u56fe\u751f\u6210\u6a21\u578b\u8fdb\u884c\u4e86\u5168\u9762\u7684\u8c03\u67e5\uff0c\u5c06\u73b0\u6709\u6a21\u578b\u5212\u5206\u4e3a\u4e94\u5927\u7c7b\uff0c\u5e76\u5206\u522b\u8fdb\u884c\u4e86\u8be6\u5c3d\u7684…<\/p>\n","protected":false},"author":1,"featured_media":23397,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[1],"tags":[],"special":[],"_links":{"self":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/23406"}],"collection":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=23406"}],"version-history":[{"count":0,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/posts\/23406\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=\/wp\/v2\/media\/23397"}],"wp:attachment":[{"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=23406"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=23406"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=23406"},{"taxonomy":"special","embeddable":true,"href":"https:\/\/swarma.org\/index.php?rest_route=%2Fwp%2Fv2%2Fspecial&post=23406"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}