{"id":27095,"date":"2021-06-19T18:21:50","date_gmt":"2021-06-19T10:21:50","guid":{"rendered":"https:\/\/swarma.org\/?p=27095"},"modified":"2021-06-19T18:21:50","modified_gmt":"2021-06-19T10:21:50","slug":"nature%e9%80%9a%e8%ae%af%ef%bc%9a%e7%bd%91%e7%bb%9c%e5%b5%8c%e5%85%a5%e7%9a%84%e6%9c%80%e4%bc%98%e7%bb%b4%e5%ba%a6%e5%88%a4%e5%ae%9a","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=27095","title":{"rendered":"Nature\u901a\u8baf\uff1a\u7f51\u7edc\u5d4c\u5165\u7684\u6700\u4f18\u7ef4\u5ea6\u5224\u5b9a"},"content":{"rendered":"
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Principled approach to the selection of the embedding dimension of networks<\/span><\/p>\n<\/section>\n<\/section>\n

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1. \u7f51\u7edc\u5d4c\u5165\u53ef\u964d\u4f4e\u8868\u5f81\u7f51\u7edc\u7684\u7ef4\u5ea6<\/strong><\/strong><\/p>\n<\/section>\n

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\u4e8e\u8be5\u6587\u76f8\u5173\u7684\u7814\u7a76\uff0c\u4e00\u662f\u4ee5\u76f8\u8fd1\u7684\u57fa\u4e8e\u51e0\u4f55\u7684\u65b9\u6cd5\uff0c\u5206\u6790\u81ea\u7136\u8bed\u8a00\u4e2d\u7684\u8bcd\u5d4c\u5165[1]\uff0c\u627e\u51fa\u8bcd\u5411\u91cf\u5bf9\u7684\u6700\u4f18\u7ef4\u5ea6\uff0c\u53e6\u4e00\u4e2a\u662f\u5bf9\u793e\u4ea4\u7f51\u7edc\u5d4c\u5165\u4e2d\u7684\u4e0d\u786e\u5b9a\u6027\u8fdb\u884c\u5b9a\u91cf\u8bc4\u4f30\u53ca\u53ef\u89c6\u5316\u7684[2]\u3002\u800c\u4ece\u4fe1\u606f\u8bba\u7684\u89c6\u89d2\uff0c\u5ba1\u89c6\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e2d\u7684\u8bcd\u5d4c\u5165\u7684\u6700\u4f18\u7ef4\u5ea6\u7684\uff0c\u662f[3]\u3002<\/span><\/section>\n

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2. \u7b97\u6cd5\u7b80\u4ecb<\/strong><\/strong><\/p>\n<\/section>\n

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\u5728\u771f\u5b9e\u573a\u666f\u4e0b\uff0c\u968f\u7740\u7f51\u7edc\u89c4\u6a21\u7684\u589e\u957f\uff0c\u9884\u671f\u80fd\u591f\u8868\u5f81\u7f51\u7edc\u4e2d\u5927\u90e8\u5206\u7ed3\u6784\u4fe1\u606f\u7684\u5d4c\u5165\u7ef4\u5ea6\u4e5f\u4f1a\u589e\u957f\u3002\u5982\u4f55\u627e\u5230\u4e0d\u540c\u5c3a\u5ea6\u7684\u7f51\u7edc\u6240\u5bf9\u5e94\u7684\u6700\u5c0f\u5d4c\u5165\u7ef4\u5ea6\uff0c\u662f\u8be5\u7814\u7a76\u8981\u89e3\u51b3\u7684\u6838\u5fc3\u95ee\u9898\u3002\u901a\u8fc7\u91c7\u7528\u6210\u5bf9\u5185\u79ef<\/span>\uff08Pairwise Inner Product PIP\uff09<\/span>\uff0c\u8be5\u7814\u7a76\u63d0\u51fa\u4e00\u4e2a\u786e\u5b9a\u4e00\u4e2a\u9002\u5408\u5d4c\u5165\u7ef4\u6570\u503c\u7684\u65b9\u6cd5\uff0c\u6307\u51fa\u6700\u4f18\u7684\u5d4c\u5165\u7ef4\u5ea6\uff0c\u5904\u4e8e\u504f\u5dee<\/span>\uff08variance\uff09<\/span>\u548c\u8bef\u5dee<\/span>\uff08bias\uff09<\/span>\u7684\u6700\u4f18\u5e73\u8861\u5904\uff0c\u800c\u5d4c\u5165\u7ef4\u5ea6\u5347\u9ad8\u4e0e\u5bf9\u5e94\u7684\u7ed3\u6784\u4fe1\u606f\u5448\u5e42\u5f8b\u5206\u5e03\u3002<\/span><\/section>\n


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\u8be5\u6587\u901a\u8fc7\u5b9a\u4e49\u4efb\u610f\u8282\u70b9\u4e4b\u95f4\u7684\u51e0\u4f55\u8ddd\u79bb\u5e76\u8ba1\u7b97\u4efb\u610f\u5d4c\u5165\u7ef4\u5ea6\u4e0e\u6700\u4f18\u5d4c\u5165\u7ef4\u5ea6\u4e4b\u95f4\u5dee\u503c\u7684\u65b9\u5f0f\uff0c\u5728\u4e0d\u540c\u7f51\u7edc\uff0c\u4e0d\u540c\u5d4c\u5165\u7b97\u6cd5\u4e2d\u53d1\u73b0\u4e86\u7f51\u7edc\u5d4c\u5165\u8bef\u5dee\u7684\u4e0b\u964d\u66f2\u7ebf\u4e0e\u94fe\u8def\u9884\u6d4b\u3001\u793e\u56e2\u5212\u5206\u3001\u8282\u70b9\u5206\u7c7b\u7684\u51c6\u786e\u7387\u4e0a\u5347\u66f2\u7ebf\u5177\u6709\u826f\u597d\u7684\u5bf9\u5e94\u5173\u7cfb\u3002\u7f51\u7edc\u5d4c\u5165\u7684\u8bef\u5dee\u968f\u5d4c\u5165\u7ef4\u5ea6\u7684\u5206\u5e03\u670d\u4ece\u5e42\u7387\u5206\u5e03\u3002<\/span><\/section>\n


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3. \u6700\u4f18\u5d4c\u5165\u7ef4\u5ea6\u5bf9\u5e94\u4e86\u9884\u6d4b\u4efb\u52a1\u7684\u9971\u548c\u70b9<\/strong><\/strong><\/p>\n<\/section>\n

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\u4e3a\u4e86\u8bc4\u4f30\u4e0d\u540c\u5d4c\u5165\u7ef4\u5ea6\u9020\u6210\u7684\u4fe1\u606f\u635f\u5931\uff0c\u901a\u8fc7\u5bf9\u5305\u542b135\u4e2a\u8282\u70b9\u7684\u7f8e\u56fd\u5927\u5b66\u6a44\u6984\u7403\u7f51\u7edc\uff0c\u4f7f\u7528node2vec\u548cLINE\u4e24\u79cd\u5d4c\u5165\u65b9\u6cd5\uff0c\u5224\u65ad\u968f\u7740\u7f51\u7edc\u5d4c\u5165\u7ef4\u5ea6\u7684\u589e\u52a0\uff0c\u5176\u6807\u51c6\u5316\u540e\u7684\u5d4c\u5165\u635f\u5931\u51fd\u6570<\/span>\uff08normalized embedding loss function\uff09<\/span>\u7684\u53d8\u5316\u60c5\u51b5\uff0c\u5982\u4e0b\u56fea\u6240\u793a\u3002\u5176\u4e2d\u84dd\u8272\u70b9\u5bf9\u5e94\u7684node2vec\u7b97\u6cd5\u548c\u7406\u8bba\u9884\u671f\u7684\u7ed3\u679c\u4e00\u81f4\uff0c\u800cLINE\u7b97\u6cd5\u548c\u7406\u8bba\u9884\u671f\u7684\u5dee\u5f02\uff0c\u6307\u51fa\u4e86\u7b97\u6cd5\u7279\u5f02\u6027\u7684\u5f71\u54cd\u3002\u6ce8\u610fnode2vec\u7b97\u6cd5\u5728\u7ef4\u5ea6\u66f4\u4f4e\u65f6\uff0c\u635f\u5931\u51fd\u6570\u7684\u4e0b\u964d\u66f4\u5feb\uff0c\u4f46\u8fd9\u4e0d\u610f\u5473\u7740\u8be5\u7b97\u6cd5\u80fd\u591f\u66f4\u597d\u7684\u8868\u5f81\u7f51\u7edc\u4fe1\u606f\uff0c\u56e0\u4e3a\u4fe1\u606f\u635f\u5931\u7684\u5b9a\u4e49\u662f\u548c\u5177\u4f53\u7b97\u6cd5\u76f8\u5173\u7684\uff0c\u5176\u4e0b\u964d\u901f\u5ea6\u7684\u5bf9\u6bd4\u4e0d\u80fd\u6307\u793a\u5d4c\u5165\u7b97\u6cd5\u7684\u597d\u574f\u3002<\/span><\/section>\n
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\u56fe1. a,American college football\u7f51\u7edc\u4f7f\u7528\u4e0d\u540c\u7684\u5d4c\u5165\u7ef4\u5ea6\uff0c\u5176\u4fe1\u606f\u635f\u5931\u7684\u4e0b\u964d\u66f2\u7ebf;c,\u57fa\u4e8enode2vec\u7b97\u6cd5\u4e0d\u540c\u7ef4\u5ea6\u7684\u5d4c\u5165\u8fdb\u884c\u94fe\u8def\u9884\u6d4b\u65f6\u7684\u51c6\u786e\u5ea6\u8bc4\u4f30\u66f2\u7ebf<\/span>
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\u800c\u5bf9Cora\u5f15\u6587\u7f51\u7edc\u8fdb\u884c\u7f51\u7edc\u5d4c\u5165\u65f6\uff0c\u53d1\u73b0\u4e86\u76f8\u540c\u7684\u8d8b\u52bf\u3002\u8003\u8651\u5230LINE\u662f\u9488\u5bf9\u5927\u89c4\u6a21\u7f51\u7edc\u5d4c\u5165\u4f18\u5316\u8fc7\u7684\u7b97\u6cd5\uff0c\u5176\u80fd\u591f\u5728\u76f8\u540c\u7684\u7ef4\u5ea6\u4e0b\uff0c\u66f4\u663e\u8457\u7684\u964d\u4f4e\u4fe1\u606f\u635f\u5931\u3002<\/span><\/section>\n
       <\/span>\u56fe2. \u4e0a\u8ff0\u7684\u4e24\u79cd\u7f51\u7edc\u4e2d\uff0c\u57fa\u4e8e\u4e0d\u540c\u7ef4\u5ea6\u7684\u5d4c\u5165\u8fdb\u884c\u94fe\u8def\u9884\u6d4b\u65f6\u7684\u51c6\u786e\u5ea6\u8bc4\u4f30\u66f2\u7ebf<\/span><\/section>\n


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\u94fe\u8def\u9884\u6d4b\u4efb\u52a1\u4e2d\uff0cAmerican college football\u4f7f\u752810\u7ef4\u6216\u8005\u66f4\u5c0f\u7684\u7ef4\u5ea6\uff0c\u5c31\u80fd\u591f\u4ee5\u8f83\u597d\u7684\u51c6\u786e\u5ea6\u8fdb\u884c\u9884\u6d4b\uff0c\u800c\u5728\u8fd9\u4e2a\u7ef4\u5ea6\uff0c\u751a\u81f3\u5728\u6b64\u4e4b\u524d\uff0c\u76f8\u5bf9\u635f\u5931\u51fd\u6570\u5c31\u5f00\u59cb\u9971\u548c\uff0c\u8fd9\u610f\u5473\u7740\u94fe\u8def\u9884\u6d4b\u4efb\u52a1\u5e76\u6ca1\u6709\u7528\u5230\u5168\u90e8\u7f51\u7edc\u5d4c\u5165\u6240\u7f16\u7801\u7684\u7ed3\u6784\u4fe1\u606f\u3002<\/span><\/section>\n

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4. \u6700\u4f18\u5d4c\u5165\u70b9\u7684\u7b97\u6cd5\u662f\u7a33\u5b9a\u7684<\/strong><\/strong><\/p>\n<\/section>\n

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<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/h3>\n


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\u5f53\u6211\u4eec\u5bf9\u6a21\u62df\u7f51\u7edc\uff0c\u8fdb\u884c\u51e0\u4f55\u5d4c\u5165<\/span>\uff08geometric embedding \uff09<\/span>\u65f6\uff0c\u4e5f\u80fd\u53d1\u73b0\u7c7b\u4f3c\u7684\u89c4\u5f8b\uff0c\u5373\u9884\u4f30\u7684\u635f\u5931\u548c\u5b9e\u9645\u57fa\u672c\u4e00\u81f4\uff0c\u4e14\u8be5\u66f2\u7ebf\u80fd\u591f\u5bf9\u5e94<\/span>\uff08\u63d0\u524d\u6307\u793a\uff09<\/span>\u9884\u6d4b\u4efb\u52a1\u4e0a\u7684\u6027\u80fd\u9971\u548c<\/span>\uff08saturation\uff09<\/span>\u70b9\u3002<\/span><\/section>\n
      <\/span><\/section>\n

\u56fe3. \u5728\u6a21\u62df\u7684\u968f\u673a\u5757\uff08stochastic block\uff09\u6a21\u578b\u4e2d\uff0c\u5d4c\u5165\u7ef4\u5ea6\u548c\u4fe1\u606f\u635f\u5931\u7684\u6563\u70b9\u56fe\u5448\u73b0\u7c7b\u4f3c\u7684\u89c4\u5f8b<\/span><\/p>\n

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\u56fe4. \u793e\u7fa4\u68c0\u6d4b\uff08community detection\uff09\u7b97\u6cd5\u5728\u4e0d\u540c\u7ef4\u5ea6\u7684\u5d4c\u5165\u4e0b\u7684\u5e73\u5747\u8868\u73b0\u60c5\u51b5\uff0c\u5176\u4e2d\u8868\u73b0\u6700\u4f18\u7684\u7ef4\u5ea6\uff0c\u540c\u6837\u51fa\u73b0\u5728\u4fe1\u606f\u635f\u5931\u51fd\u6570\u5448\u73b0\u9971\u548c\u503c\u4e4b\u524d<\/span><\/p>\n


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\u5728BA\u6a21\u578b\u7684\u6a21\u62df\u6570\u636e\u4e2d\uff0c\u4e0d\u540c\u5927\u5c0f\u548c\u8282\u70b9\u5bc6\u5ea6\u7684\u7f51\u7edc\uff0c\u5176\u5bf9\u5e94\u7684\u53c2\u6570\u5982\u4e0b\u6240\u793a\uff0c\u8be5\u56fe\u8bf4\u660e\u4e86\u8be5\u7b97\u6cd5\u5728\u4e0d\u540c\u7c7b\u578b\u7684\u7f51\u7edc\u4e0b\u7684\u53c2\u6570\u7a33\u5b9a\u6027\u3002<\/span><\/section>\n
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\u56fe5. BA\u6a21\u62df\u7f51\u7edc\u5927\u5c0f\u548c\u5bc6\u5ea6\u548c\u6700\u4f18\u5d4c\u5165\u7ef4\u5ea6\u53c2\u6570\u7684\u5bf9\u5e94\u5173\u7cfb<\/span><\/p>\n


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\u800c\u5728\u8fd0\u884c\u591a\u6b21\u5d4c\u5165\u7b97\u6cd5\uff0c\u901a\u8fc7\u4e0d\u540c\u8fd0\u884c\u7ed3\u679c\u7684\u65b9\u5dee<\/span>\uff08\u53c8\u79f0\u4e3aembedding coherence\uff09<\/span>\uff0c\u6765\u8bc4\u4ef7\u5d4c\u5165\u7b97\u6cd5\u968f\u673a\u6027\u7684\u5f71\u54cd\u65f6\uff0c\u4f1a\u53d1\u73b0\u5176\u7ed3\u679c\u76f8\u5bf9\u7a33\u5b9a\uff0c\u5c24\u5176\u662f\u5728\u8f83\u9ad8\u7684\u5d4c\u5165\u7ef4\u5ea6\u65f6\u3002<\/span><\/section>\n
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\u56fe6. \u4f7f\u7528\u4e0d\u540c\u7ef4\u5ea6\u7684\u5d4c\u5165\u65f6\uff0cAmerican college football\u7f51\u7edc\u548cCora\u5f15\u6587\u7f51\u7edc\u7684embedding coherence \u968f\u5d4c\u5165\u7ef4\u5ea6\u7684\u53d8\u5316\u6563\u70b9\u56fe<\/span><\/p>\n


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Embedding coherence \u968f\u5d4c\u5165\u7ef4\u5ea6\u589e\u52a0\u5355\u8c03\u4e0b\u964d\uff0c\u8fd9\u7ed3\u5408\u4e4b\u524d\u53d1\u73b0\u7684\u7f51\u7edc\u4e2d\u94fe\u8def\u9884\u6d4b\uff0c\u56fe\u805a\u7c7b\u4efb\u52a1\u6240\u9700\u7684\u7ef4\u5ea6\uff0c\u4f4e\u4e8e\u6700\u4f18\u5d4c\u5165\u7ef4\u5ea6\uff0c\u53ef\u89e3\u91ca\u4e3a\u4f55\u4f7f\u7528\u6bd4\u6700\u4f18\u7ef4\u5ea6\u9ad8\u7684\u7ef4\u5ea6\u8fdb\u884c\u5d4c\u5165\u65f6\uff0c\u9884\u6d4b\u6548\u679c\u4e0d\u4f1a\u53d8\u5dee\u3002<\/span><\/section>\n


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\u4ee5\u4e0a\u5b9e\u9a8c\uff0c\u7efc\u5408\u8d77\u6765\u8bba\u8bc1\u4e86\u8be5\u65b9\u6cd5\u627e\u51fa\u7684\u6700\u4f18\u7ef4\u5ea6\u662f\u53ef\u9760\u7684\u3002<\/span><\/section>\n

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5. \u771f\u5b9e\u7f51\u7edc\u7684\u5d4c\u5165\u7ef4\u5ea6\u8fdc\u5c0f\u4e8e\u8282\u70b9\u6570\u76ee<\/strong><\/strong><\/p>\n<\/section>\n

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\u5927\u578b\u7f51\u7edc\u7684\u5b9e\u9a8c\u7ed3\u679c<\/span>\uff08\u7814\u7a76\u7684\u666e\u904d\u6027\uff09<\/span>\u4ee5\u4e0a\u5b9e\u9a8c\uff0c\u8bba\u8bc1\u4e86\u8be5\u65b9\u6cd5\u627e\u51fa\u7684\u6700\u4f18\u7ef4\u5ea6\u662f\u53ef\u9760\u7684\uff0c\u800c\u5c06\u8be5\u65b9\u6cd5\u5e94\u7528\u4e8e135\u4e2a\u771f\u5b9e\u4e16\u754c\u4e2d\u7684\u7f51\u7edc\uff0c\u8be5\u7814\u7a76\u53d1\u73b0\u5927\u591a\u6570\u60c5\u51b5\u4e0b\uff0c\u9884\u4f30\u7684\u6700\u4f18\u7ef4\u5ea6\u8fdc\u8fdc\u5c0f\u4e8e\u5b9e\u9645\u7f51\u7edc\u4e2d\u7684\u8282\u70b9\u6570\uff0c\u867d\u7136\u8be5\u65b9\u6cd5\u5e76\u4e0d\u80fd\u6392\u9664\u5b58\u5728\u4e00\u4e2a\u5bf9\u8fd9\u4e9b\u7f51\u7edc\u66f4\u4f18\u7684\u8868\u5f81\u65b9\u6cd5\uff0c\u80fd\u591f\u4ee5\u66f4\u4f4e\u7684\u7ef4\u5ea6\u65e0\u635f\u5730\u8868\u5f81\u7f51\u7edc\u4e2d\u7684\u7ed3\u6784\u4fe1\u606f\uff0c\u4f46\u8be5\u7814\u7a76\u6307\u51fa\u4e86\u53ef\u8868\u5f81\u7f51\u7edc\u7ed3\u6784\u4fe1\u606f\u7684\u7ef4\u5ea6\u901a\u5e38\u504f\u4f4e\u3002<\/span><\/section>\n
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\u56fe7. \u56fea\u548c\u56feb135\u4e2a\u771f\u5b9e\u7f51\u7edc\u4e0b\u7684\u6a21\u578b2\u4e2a\u53c2\u6570\u5206\u5e03\u56fe\uff0c\u56fec\uff0c\u771f\u5b9e\u7f51\u7edc\u7684\u6700\u4f18\u5d4c\u5165\u7ef4\u5ea6\u7684\u7d2f\u79ef\u5bc6\u5ea6\u5206\u5e03\uff0c\u5176\u4e2d\u5927\u90e8\u5206\u7684\u6700\u4f18\u7ef4\u5ea6\u90fd\u5c0f\u4e8e20<\/span>
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\u603b\u7ed3\u6765\u770b\uff0c\u8be5\u7814\u7a76\u539f\u521b\u6027\u7684\u4ece\u51e0\u4f55\u89c6\u89d2\u5ba1\u89c6\u7f51\u7edc\u5d4c\u5165\uff0c\u627e\u51fa\u4e86\u4e00\u79cd\u901a\u7528\u7684\u8bc4\u4ef7\u7f51\u7edc\u5185\u5728\u7ef4\u5ea6\u7684\u65b9\u6cd5\uff0c\u5176\u7ed3\u679c\u548c\u8c31\u805a\u7c7b\u9884\u6d4b\u7684\u7406\u8bba\u503c\u76f8\u8fd1\u3002\u4f5c\u8005\u53d1\u73b0\u5927\u90e8\u5206\u771f\u5b9e\u7684\u7f51\u7edc\uff0c\u90fd\u53ef\u4ee5\u7528\u8fdc\u5c0f\u4e8e\u5176\u8282\u70b9\u6570\u7684\u7ef4\u5ea6\u8868\u793a\u3002\u901a\u8fc7\u8be5\u65b9\u6cd5\u9884\u6d4b\u7684\u6700\u4f18\u5d4c\u5165\u7ef4\u5ea6\uff0c\u80fd\u591f\u6307\u51fa\u5728\u4e0b\u6e38\u5206\u6790\u4e2d\uff0c\u4f55\u65f6\u4f1a\u8868\u73b0\u5f97\u66f4\u597d\uff0c\u4ece\u800c\u51cf\u5c11\u4e86\u8bd5\u9519\u6210\u672c\u3002<\/span><\/section>\n

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\u53c2\u8003\u8d44\u6599\uff1a<\/span><\/strong><\/span><\/section>\n

[1] On the Dimensionality of Word Embedding<\/span>
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[2] Latent Space Approaches to Social Network Analysis<\/span><\/p>\n

[3] Word2vec Skip-gram Dimensionality Selection via Sequential Normalized Maximum Likelihood<\/span><\/p>\n


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\u590d\u6742\u79d1\u5b66\u6700\u65b0\u8bba\u6587<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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\u96c6\u667a\u6591\u56fe\u9876\u520a\u8bba\u6587\u901f\u9012\u680f\u76ee\u4e0a\u7ebf\u4ee5\u6765\uff0c\u6301\u7eed\u6536\u5f55\u6765\u81eaNature\u3001Science<\/span>\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<\/span>
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\u63a8\u8350\u9605\u8bfb<\/span><\/strong><\/strong><\/p>\n