{"id":33119,"date":"2022-03-14T21:09:14","date_gmt":"2022-03-14T13:09:14","guid":{"rendered":"https:\/\/swarma.org\/?p=33119"},"modified":"2022-03-14T21:09:14","modified_gmt":"2022-03-14T13:09:14","slug":"%e6%8e%a8%e8%8d%90%e7%b3%bb%e7%bb%9f%e4%b8%ad%e7%9a%84%e5%9b%a0%e6%9e%9c%e5%ad%a6%e4%b9%a0%ef%bc%9a%e5%9f%ba%e7%a1%80%e3%80%81%e4%bc%b0%e8%ae%a1%e3%80%81%e9%a2%84%e6%b5%8b%e5%92%8c%e6%8c%91%e6%88%98","status":"publish","type":"post","link":"https:\/\/swarma.org\/?p=33119","title":{"rendered":"\u63a8\u8350\u7cfb\u7edf\u4e2d\u7684\u56e0\u679c\u5b66\u4e60\uff1a\u57fa\u7840\u3001\u4f30\u8ba1\u3001\u9884\u6d4b\u548c\u6311\u6218"},"content":{"rendered":"
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\u7814\u7a76\u9886\u57df\uff1a\u57fa\u4e8e\u56e0\u679c\u63a8\u7406\u7684\u63a8\u8350\u7cfb\u7edf\uff0c\u56e0\u679c\u5b66\u4e60<\/strong><\/strong><\/span><\/strong><\/span><\/strong><\/span><\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n

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\u674e\u660a\u8f69<\/span> <\/span>| \u4f5c\u8005<\/strong><\/span><\/strong><\/p>\n

\u9093\u4e00\u96ea<\/span> | \u7f16\u8f91<\/strong><\/span>
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\u8bba\u6587\u9898\u76ee\uff1a<\/span><\/p>\n

<\/span>Causal Analysis Framework for Recommendation<\/span><\/p>\n

\u8bba\u6587\u94fe\u63a5\uff1a<\/span><\/p>\n

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\u8fd1\u5e74\u6765\uff0c\u57fa\u4e8e\u56e0\u679c\u63a8\u7406\u7684\u63a8\u8350\u7cfb\u7edf<\/span>\uff08RS\uff09<\/span>\u5728\u5de5\u4e1a\u754c\u83b7\u5f97\u4e86\u5e7f\u6cdb\u7684\u5173\u6ce8\uff0c\u5e76\u5728\u8bb8\u591a\u9884\u6d4b\u548c\u53bb\u504f\u4efb\u52a1\u4e2d\u8868\u73b0\u51fa\u4e86\u826f\u597d\u7684\u6548\u679c\u3002\u7136\u800c\uff0c\u4e00\u4e2a\u7edf\u4e00\u7684\u56e0\u679c\u5206\u6790\u6846\u67b6\u8fd8\u672a\u5efa\u7acb\u3002\u8bb8\u591a\u57fa\u4e8e\u56e0\u679c\u5173\u7cfb\u7684\u9884\u6d4b\u548c\u53bb\u504f\u7814\u7a76\u5f88\u5c11\u8ba8\u8bba\u5404\u79cd\u504f\u501a\u7684\u56e0\u679c\u89e3\u91ca\u548c\u76f8\u5e94\u56e0\u679c\u5047\u8bbe\u7684\u5408\u7406\u6027\u3002\u5728\u672c\u6587\u4e2d\uff0c\u6211\u4eec\u9996\u5148\u63d0\u4f9b\u4e86\u4e00\u4e2a\u6b63\u5f0f\u7684\u56e0\u679c\u5206\u6790\u6846\u67b6\u6765\u7efc\u8ff0\u548c\u7edf\u4e00\u73b0\u6709\u7684\u56e0\u679c\u542f\u53d1\u7684\u63a8\u8350\u65b9\u6cd5\uff0c\u5b83\u53ef\u4ee5\u9002\u5e94 RS \u4e2d\u7684\u4e0d\u540c\u573a\u666f\u3002\u7136\u540e\uff0c\u6211\u4eec\u63d0\u51fa\u4e86\u4e00\u4e2a\u65b0\u7684\u5206\u7c7b\u6cd5\uff0c\u5e76\u4ece\u8fdd\u53cd\u56e0\u679c\u5206\u6790\u5047\u8bbe\u7684\u89d2\u5ea6\u7ed9\u51fa\u4e86 RS \u4e2d\u5404\u79cd\u504f\u501a\u7684\u6b63\u5f0f\u56e0\u679c\u5b9a\u4e49\u3002\u6700\u540e\uff0c\u6211\u4eec\u5bf9 RS \u4e2d\u7684\u8bb8\u591a\u53bb\u504f\u548c\u9884\u6d4b\u4efb\u52a1\u8fdb\u884c\u4e86\u5f62\u5f0f\u5316\uff0c\u5e76\u603b\u7ed3\u4e86\u57fa\u4e8e\u7edf\u8ba1\u548c\u673a\u5668\u5b66\u4e60\u7684\u56e0\u679c\u4f30\u8ba1\u65b9\u6cd5\uff0c\u671f\u671b\u4e3a\u56e0\u679c RS \u793e\u533a\u63d0\u4f9b\u65b0\u7684\u7814\u7a76\u673a\u4f1a\u548c\u89c6\u89d2\u3002<\/span><\/p>\n


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2. \u56e0\u679c\u5206\u6790\u6846\u67b6<\/strong><\/strong><\/p>\n<\/section>\n

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\u6211\u4eec\u63d0\u51fa\u7684\u56e0\u679c\u5206\u6790\u6846\u67b6<\/span>\uff08\u5206\u6790\u6d41\u7a0b\uff09<\/span>\u7531\u4ee5\u4e0b\u4e09\u6b65\u6784\u6210\uff1a(1) \u5b9a\u4e49\u56e0\u679c\u4f30\u8ba1\u91cf<\/span> (\u56e0\u679c\u53c2\u6570) <\/span>\u4ee5\u56de\u7b54\u79d1\u5b66\u95ee\u9898\uff1b(2) \u7ed9\u5b9a\u6570\u636e\u540e\uff0c\u8ba8\u8bba\u56e0\u679c\u4f30\u8ba1\u91cf\u7684\u53ef\u6062\u590d\u6027\uff1b(3) \u5efa\u7acb\u6a21\u578b\uff0c\u5f97\u5230\u5f85\u4f30\u8ba1\u91cf\u7684\u76f8\u5408\u4f30<\/span>\u8ba1\u3002<\/span>\u56fe 1 \u63cf\u8ff0\u4e86\u8fd9\u4e00\u56e0\u679c\u5206\u6790\u6846\u67b6\u3002<\/span><\/p>\n


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\u56fe1: \u56e0\u679c\u5206\u6790\u6846\u67b6<\/span><\/p>\n


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\u5178\u578b\u7684\u56e0\u679c\u63a8\u65ad\u65b9\u6cd5\u5728\u6536\u96c6\u6570\u636e\u4e4b\u524d\uff0c\u5148\u5c06\u6240\u7814\u7a76\u7684\u79d1\u5b66\u95ee\u9898\u8f6c\u5316\u4e3a\u56e0\u679c\u4f30\u8ba1\u91cf\u3002\u7136\u800c\uff0cRS \u4e2d\u5f88\u5c11\u6709\u6587\u732e\u5bf9\u4f30\u8ba1\u91cf\u6709\u660e\u786e\u7684\u8bf4\u660e\u3002\u901a\u8fc7\u5c06\u79d1\u5b66\u95ee\u9898\u5f62\u5f0f\u5316\u4e3a\u56e0\u679c\u4f30\u8ba1\uff0c\u6211\u4eec\u53ef\u4ee5\u56de\u7b54\u4ee5\u4e0b\u95ee<\/span>\u9898\uff1a\u7a76\u7adf\u662f\u4ec0\u4e48\u88ab\u4f30\u8ba1\u4ee5\u53ca\u51fa\u4e8e\u4ec0\u4e48\u76ee\u7684\u3002\u63a5\u4e0b\u6765\uff0c\u6211\u4eec\u8ba8\u8bba\u5728\u6536\u96c6\u5230\u89c2\u5bdf\u6570\u636e\u540e\uff0c\u4f30\u8ba1\u91cf\u80fd\u5426\u5728\u9002\u5f53\u7684\u5047\u8bbe\u4e0b\u88ab\u4f30\u8ba1\u51fa\uff0c\u5373\u4f30\u8ba1\u91cf\u7684\u53ef\u6062\u590d\u6027\u3002<\/span><\/p>\n


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\u53ef\u6062\u590d\u6027\u662f\u56e0\u679c\u63a8\u65ad\u7684\u5173\u952e\u8981\u7d20\uff0c\u800c\u5b83\u5728\u63a8\u8350\u7cfb\u7edf\u4e2d\u5f88\u5c11\u88ab\u8ba8\u8bba\u3002\u8ba8\u8bba\u53ef\u6062\u590d\u6027\u7684\u610f\u4e49\u81f3\u5c11\u662f\u53cc\u91cd\u7684\uff1a\u9996\u5148\uff0c\u6211\u4eec\u53ef\u4ee5\u786e\u5b9a\u4e00\u4e2a\u53cd\u4e8b\u5b9e\u4f30\u8ba1\u91cf\u5728\u4e00\u4e9b\u5408\u7406\u7684\u5047\u8bbe\u4e0b\u662f\u5426\u80fd\u591f\u88ab\u4f30\u8ba1\u51fa\u3002\u82e5\u4e0d\u53ef\u6062\u590d\uff0c\u5219\u9700\u8981\u8003\u8651\u6536\u96c6\u66f4\u591a\u7684\u65b0\u6570\u636e\u3002\u5176\u6b21\uff0c\u5982\u679c\u4f30\u8ba1\u662f\u53ef\u6062\u590d\u7684\uff0c\u6211\u4eec\u53ef\u4ee5\u660e\u786e\u5730\u5448\u73b0\u83b7\u5f97\u53ef\u6062\u590d\u6027\u6240\u9700\u7684\u5047\u8bbe\u3002\u6211\u4eec\u53ef\u4ee5\u901a\u8fc7\u8bc4\u4f30\u5047\u8bbe\u7684\u5408\u7406\u6027\u6765\u8bc4\u4f30\u7ea0\u504f\u65b9\u6cd5\u7684\u597d\u574f\uff1b\u4e5f\u53ef\u4ee5\u901a\u8fc7\u5f31\u5316\u5047\u8bbe\u6761\u4ef6\uff0c\u6765\u63d0\u51fa\u4e00\u4e9b\u65b0\u7684\u7ea0\u504f\u65b9\u6cd5\u3002\u4ee5\u4e0b 5 \u4e2a\u5047\u8bbe\u662f\u56e0\u679c\u63a8\u8350\u4e2d\u5e38\u7528\u7684\u53ef\u6062\u590d\u6027\u5047\u8bbe\u3002<\/span><\/p>\n

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    \u5047\u8bbe 1 (SUTVA): (a) \u65e0\u591a\u7248\u672c\u5904\u7406\uff1b(b) \u65e0\u4ea4\u4e92\u3002<\/span><\/p>\n<\/li>\n

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    \u5047\u8bbe 2 (\u4e00\u81f4\u6027\uff0cConsistency): <\/sub>\uff0c \u5bf9\u4efb\u610f<\/sub>\u3002<\/span><\/section>\n<\/li>\n
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    \u5047\u8bbe 3 (\u6b63\u6570\u6027\uff0cPositivity): <\/sub>\uff0c \u5bf9\u4efb\u610f t, x\u3002<\/span><\/section>\n<\/li>\n
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    \u5047\u8bbe 4 (\u6761\u4ef6\u53ef\u4ea4\u6362\u6027, Conditional exchangeability): Y (t) \u22a5 T | X, \u5bf9\u4efb\u610f<\/span><\/sub><\/span> \u3002\u4e00\u4e2a\u66f4\u5f3a\u7684\u7248\u672c\u4e3a\u53ef\u4ea4\u4e92\u6027 (exchangeability): Y (t) \u22a5 T , \u5bf9\u4efb\u610f<\/span><\/sub><\/span> \u3002<\/span><\/section>\n<\/li>\n
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    \u5047\u8bbe 5 (\u968f\u673a\u62bd\u6837\uff0cRandom sampling): <\/sub>\uff0c\u5176\u4e2d<\/sub>\u8868\u793a\u76ee\u6807\u603b\u4f53\u5206\u5e03\uff0c <\/sub><\/span>\u8868\u793a\u89c2\u6d4b\u6837\u672c\u5206\u5e03\u3002<\/span><\/section>\n<\/li>\n<\/ul>\n

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    \u9700\u5f3a\u8c03\u7684\u662f\uff0cRS \u4e2d\u4e0d\u540c\u7684\u56e0\u679c\u95ee\u9898\u5bf9\u5e94\u4e8e\u4e0d\u540c\u7684\u56e0\u679c\u4f30\u8ba1\u91cf\uff0c\u7ed9\u5b9a\u6536\u96c6\u7684\u6570\u636e\u540e\uff0c\u4f1a\u906d\u53d7\u4e0d\u540c\u7c7b\u578b\u7684\u504f\u501a\u5f71\u54cd\uff0c\u9700\u8981\u91c7\u7528\u5404\u79cd\u4e0d\u540c\u7684\u5047\u8bbe\u548c\u6a21\u578b\u6765\u4f30\u8ba1\u56e0\u679c\u53c2\u6570\uff0c\u8fdb\u800c\u56de\u7b54\u79d1\u5b66\u95ee\u9898\u3002<\/span><\/section>\n

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    3. \u5173\u4e8e\u63a8\u8350\u7cfb\u7edf\u4e2d\u504f\u501a\u7684\u65b0\u89c1\u89e3<\/strong><\/strong><\/p>\n<\/section>\n

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    \u7834\u574f\u5047\u8bbe 1-5 \u4f1a\u5bfc\u81f4\u5404\u79cd\u5404\u6837\u7684\u504f\u501a\u3002\u5c3d\u7ba1\u8fd9\u4e9b\u504f\u501a\u5728\u63a8\u8350\u7cfb\u7edf\u793e\u533a\u4e2d\u6709\u8fc7\u8ba8\u8bba [3], \u5173\u4e8e\u504f\u501a\u7684\u660e\u786e\u5b9a\u4e49\u4ecd\u4e0d\u6e05\u6670\uff0c\u8fd9\u4e25\u91cd\u5730\u5236\u7ea6\u4e86\u53bb\u504f\u65b9\u6cd5\u7684\u53d1\u5c55\u3002\u5728\u672c\u8282\u4e2d\uff0c\u6211\u4eec\u4ece\u7834\u574f\u56e0\u679c\u63a8\u65ad\u7684\u5047\u8bbe\u51fa\u53d1\uff0c\u63d0\u51fa\u5173\u4e8e\u63a8\u8350\u7cfb\u7edf\u4e2d\u504f\u501a\u7684\u65b0\u89c1\u89e3\uff0c\u89c1\u8868 1\u3002<\/span><\/section>\n

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    \u8868 1: \u5173\u4e8e\u504f\u501a\u7684\u65b0\u89c1\u89e3<\/span><\/section>\n
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    3.1 \u6df7\u6742\u504f\u501a\u548c\u9009\u62e9\u504f\u501a<\/span><\/strong><\/span><\/h2>\n


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    \u5728\u56e0\u679c\u63a8\u65ad\u9886\u57df\uff0c\u5b9e\u73b0\u56e0\u679c\u4f30\u8ba1\u7684\u4e24\u4e2a\u6700\u5e38\u89c1\u7684\u969c\u788d\u662f\u6df7\u6742\u504f\u501a\u548c\u9009\u62e9\u504f\u501a [4]\uff0c\u6211\u4eec\u4e25\u683c\u5b9a\u4e49\u8fd9\u4e24\u79cd\u504f\u501a\u3002<\/span><\/section>\n

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    \u5b9a\u4e49 1 (\u6df7\u6742\u504f\u501a)\u3002\u6df7\u6742\u504f\u501a\u6307\u7531\u4e8e\u5b58\u5728\u67d0\u4e9b\u540c\u65f6\u5f71\u54cd\u5904\u7406\u548c\u7ed3\u5c40\u7684\u56e0\u7d20\u800c\u5f15\u8d77\u7684\uff08T \u548c Y \u4e4b\u95f4\u7684\uff09\u5173\u8054\u6027 [4]\uff0c\u5373<\/sub>\u3002\u901a\u5e38\u4f1a\u5bfc\u81f4<\/span><\/section>\n

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    \u5b9a\u4e49 2 (\u9009\u62e9\u504f\u501a)\u3002\u9009\u62e9\u504f\u501a\u6307\u6837\u672c\u5206\u5e03\u4e0e\u76ee\u6807\u603b\u4f53\u7684\u5206\u5e03\u4e0d\u540c [8]\uff0c\u5373<\/span><\/section>\n

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    <\/p>\n


    <\/section>\n
    \u6df7\u6742\u504f\u501a\u7ecf\u5e38\u88ab\u5f53\u4f5c\u662f\u89c2\u5bdf\u6027\u7814\u7a76\u7684\u7f3a\u70b9\u3002\u5728\u89c2\u5bdf\u6027\u7814\u7a76\u4e2d\uff0c\u5904\u7406\u548c\u7ed3\u679c\u53ef\u80fd\u7531\u8bb8\u591a\u56e0\u7d20\u51b3\u5b9a\uff0c\u7136\u540e\u8fd9\u4e9b\u56e0\u7d20\u7684\u5f71\u54cd\u4e0e\u5904\u7406\u6548\u679c\u7ea0\u7f20<\/span>\uff08\u6216\u6df7\u6dc6\uff09<\/span>\u5728\u4e00\u8d77\uff0c\u5bfc\u81f4\u4e0d\u540c\u5904\u7406\u7ec4\u95f4\u7684\u6df7\u6742\u56e0\u7d20\u5206\u5e03\u5b58\u5728\u663e\u8457\u5dee\u5f02\u3002\u968f\u7740\u6837\u672c\u91cf\u7684\u589e\u52a0\uff0c\u6df7\u6742\u504f\u501a\u65e0\u6cd5\u6d88\u9664 [8]\u3002<\/span><\/section>\n

    <\/span><\/section>\n
    \u9009\u62e9\u504f\u501a\u5728\u63a8\u8350\u7cfb\u7edf\u4e2d\u5927\u91cf\u5b58\u5728\u3002\u4f8b\u5982\uff0c\u67d0\u4e2a\u7cfb\u7edf\u65e8\u5728\u901a\u8fc7\u8fc7\u6ee4\u6389\u9884\u6d4b\u8bc4\u5206\u8f83\u4f4e\u7684\u7269\u54c1\u6765\u63a8\u8350\u7528\u6237\u53ef\u80fd\u559c\u6b22\u7684\u7269\u54c1\uff0c\u8fd9\u79cd\u9009\u62e9\u662f\u4ee5\u524d\u7684\u6a21\u578b\u9009\u62e9\u504f\u501a [15]\uff1b\u7528\u6237\u503e\u5411\u4e8e\u8bc4\u4ef7\u4ed6\u559c\u6b22\u7684\u7269\u54c1\uff0c\u5f88\u5c11\u8bc4\u4ef7\u4ed6\u4e0d\u559c\u6b22\u7684\u9879\u76ee\uff0c\u8fd9\u662f\u7528\u6237\u7684\u81ea\u6211\u9009\u62e9\u504f\u501a\u3002\u5728\u8fd9\u79cd\u60c5\u51b5\u4e0b\uff0c\u6570\u636e\u6536\u96c6\u8fc7\u7a0b\u5c06\u53cd\u6620\u6837\u672c\u6bd4\u4f8b\u7684\u5931\u771f\uff0c\u5e76\u4e14\uff0c\u7531\u4e8e\u6570\u636e\u4e0d\u518d\u662f\u76ee\u6807\u4eba\u7fa4\u7684\u5fe0\u5b9e\u4ee3\u8868\uff0c\u5982\u6df7\u6742\u504f\u501a\u7684\u60c5\u51b5\uff0c\u65e0\u8bba\u6536\u96c6\u7684\u6837\u672c\u6570\u91cf\u5982\u4f55\uff0c\u90fd\u5c06\u4ea7\u751f\u504f\u501a\u4f30\u8ba1\u3002<\/span><\/section>\n

    <\/span><\/section>\n
    \u9009\u62e9\u4ea7\u751f\u7684\u504f\u501a\u4e0e\u6df7\u6dc6\u4ea7\u751f\u7684\u504f\u501a\u6709\u7740\u6839\u672c\u7684\u4e0d\u540c\u3002\u9009\u62e9\u504f\u501a\u6765\u81ea\u4e8e\u6837\u672c\u91c7\u96c6\u8fc7\u7a0b\u4e2d\u7684\u7cfb\u7edf\u6027\u504f\u501a [1]\u3002\u8bbe\u8ba1\u826f\u597d\u7684\u62bd\u6837\u7a0b\u5e8f\u53ef\u4ee5\u51cf\u5c11\u9009\u62e9\u504f\u501a\u3002\u76f8\u53cd\uff0c\u6df7\u6dc6\u504f\u501a\u6765\u81ea\u4e8e\u53e6\u4e00\u79cd\u7c7b\u578b\u7684\u7cfb\u7edf\u6027\u504f\u501a\uff0c\u8be5\u7cfb\u7edf\u6027\u504f\u501a\u672c\u8d28\u4e0a\u7531\u7279\u5f81\u3001\u5904\u7406\u548c\u7ed3\u679c\u4e4b\u95f4\u7684\u56e0\u679c\u673a\u5236<\/span>\uff08\u5173\u7cfb\uff09<\/span>\u51b3\u5b9a\uff0c\u4e0e\u6570\u636e\u6536\u96c6\u8fc7\u7a0b\u65e0\u5173\u3002\u5904\u7406\u5206\u914d\u7684\u968f\u673a\u5316\u53ef\u4ee5\u6d88\u9664<\/span>\uff08\u672a\u6d4b\u91cf\u7684\uff09<\/span>\u6df7\u6742\u504f\u501a\u7684\u5f71\u54cd\uff0c\u4f46\u4e0d\u80fd\u6d88\u9664\u9009\u62e9\u504f\u501a\u7684\u5f71\u54cd [4]\u3002<\/span><\/section>\n

    <\/span><\/section>\n
    \u6df7\u6742\u504f\u501a\u548c\u9009\u62e9\u504f\u501a\u95f4\u6709\u4e00\u5b9a\u7684\u8054\u7cfb\u3002\u9996\u5148\uff0c\u5b83\u4eec\u90fd\u662f\u7cfb\u7edf\u6027\u504f\u501a\uff0c\u4f1a\u5bfc\u81f4\u201c\u865a\u5047\u76f8\u5173\u6027\u201d[1]\u3002\u7b2c\u4e8c\uff0c\u5982\u679c\u6211\u4eec\u628a\u5206\u6790\u5c40\u9650\u4e8e\u975e\u7f3a\u5931\u5355\u5143\uff0c\u5219\u7f3a\u5931\u6570\u636e\u95ee\u9898\u53ef\u88ab\u89c6\u4e3a\u9009\u62e9\u504f\u501a\u3002\u6df7\u6742\u504f\u501a\u4e5f\u53ef\u4ee5\u88ab\u89c6\u4e3a\u7f3a\u5931\u6570\u636e\u95ee\u9898\u3002\u4f8b\u5982\uff0c\u8003\u8651\u4e8c\u503c\u5904\u7406\u7684\u60c5\u51b5\uff0c\u7136\u540e\u5bf9\u4e8e\u6bcf\u4e2a\u5355\u5143\uff0c\u53ea\u80fd\u89c2\u5bdf\u5230\u5176\u4e2d\u4e00\u4e2a\u6f5c\u5728\u7684\u7ed3\u679c\uff08Y (1) \u6216 Y (0)\uff09\uff0c\u53e6\u4e00\u4e2a\u6f5c\u5728\u7ed3\u679c\u53ef\u4ee5\u88ab\u8ba4\u4e3a\u662f\u7f3a\u5931\u7684\u3002<\/span><\/section>\n

    <\/section>\n

    3.2 \u63a8\u8350\u7cfb\u7edf\u4e2d\u504f\u501a\u7684\u65b0\u5206\u7c7b<\/span><\/strong><\/span><\/h2>\n


    <\/span><\/p>\n

    \u56e0\u679c\u5206\u6790\u6846\u67b6\u4e2d\u7684\u6bcf\u4e2a\u6b65\u9aa4\u90fd\u4f9d\u8d56\u4e8e\u4e00\u4e9b\u5047\u8bbe\uff0c\u8fdd\u53cd\u8fd9\u4e9b\u5047\u8bbe\u5c06\u5bfc\u81f4\u4e0d\u540c\u7c7b\u578b\u7684\u504f\u501a\u3002\u8fd9\u79cd\u89c2\u70b9\u63d0\u4f9b\u4e86\u4e00\u79cd\u7edf\u4e00\u7684\u65b9\u5f0f\u6765\u8ba8\u8bba\u63a8\u8350\u7cfb\u7edf\u4e2d\u7684\u5404\u79cd\u504f\u501a\uff0c\u5e76\u4f7f\u6211\u4eec\u80fd\u591f\u6b63\u5f0f\u5b9a\u4e49\u5b83\u4eec\u3002<\/span><\/section>\n

    <\/span><\/section>\n
    \u4ece\u63a8\u8350\u8fc7\u7a0b\u7684\u89d2\u5ea6\u6765\u770b\uff0c\u6709\u5173\u63a8\u8350\u7cfb\u7edf\u7684\u6587\u732e\u63d0\u51fa\u4e86\u5404\u79cd\u504f\u501a\uff0c\u5982\u9009\u62e9\u504f\u501a\u3001\u4ece\u4f17\u504f\u501a\u3001\u66dd\u5149\u504f\u501a\u3001\u4f4d\u7f6e\u504f\u501a\u3001\u5f52\u7eb3\u504f\u501a\u3001\u6d41\u884c\u504f\u501a [3]\u3002\u503c\u5f97\u6ce8\u610f\u7684\u662f [3] \u4e2d\u9009\u62e9\u504f\u501a\u7684\u5b9a\u4e49\u4e0e\u672c\u6587\u4e2d\u7684\u5b9a\u4e49\u4e0d\u540c\u3002\u6211\u4eec\u4f7f\u7528\u201c\u7528\u6237\u9009\u62e9\u504f\u501a\u201d\u548c\u201c\u9009\u62e9\u504f\u501a\u201d\u6765\u533a\u5206\u5b83\u4eec\u3002<\/span><\/section>\n

    <\/span><\/section>\n
    \u6df7\u6742\u504f\u501a\u548c\u9009\u62e9\u504f\u501a\u5206\u522b\u8fdd\u53cd\u53ef\u4ea4\u6362\u6027\u548c\u968f\u673a\u62bd\u6837\u5047\u8bbe\u3002\u6709\u8da3\u7684\u662f\uff0c\u6839\u636e\u504f\u501a\u7684\u63cf\u8ff0\u6027\u5b9a\u4e49\uff0c \u6d41\u884c\u504f\u501a\u3001\u7528\u6237\u9009\u62e9\u504f\u501a\u548c\u66dd\u5149\u504f\u501a\u5c06\u5bfc\u81f4 <\/sub>\uff0c\u56e0\u6b64\u5c5e\u4e8e\u9009\u62e9\u504f\u501a\u3002\u7c7b\u4f3c\u7684\u89c2\u70b9\u4e5f\u89c1\u4e8e [2]\uff0c\u5b83\u4e5f\u5c06\u4f4d\u7f6e\u504f\u501a\u4f5c\u4e3a\u4e00\u79cd\u9009\u62e9\u504f\u501a\u3002<\/span><\/section>\n

    <\/span><\/section>\n
    \u4ece\u4f17\u504f\u501a\u610f\u5473\u7740\u7528\u6237\u503e\u5411\u4e8e\u7ed9\u51fa\u4e0e\u7ec4\u4e2d\u7684\u5176\u4ed6\u4eba\u76f8\u4f3c\u7684\u8bc4\u5206\u3002\u5b83\u8fdd\u53cd\u4e86 SUTVA(b) \u5047\u8bbe\uff0c\u5373<\/span>\u65e0\u4ea4\u4e92\u4f5c\u7528\u3002\u8fd9\u662f\u56e0\u4e3a\u4ece\u4f17\u73b0\u8c61\u53ef\u80fd\u5bfc\u81f4 Ym<\/sub><\/span>(t) \u7684\u503c\u4f9d\u8d56\u4e8e\u5355\u5143 j\u2260m \u7684\u5904\u7406\u503c tj<\/sub><\/span>\u3002\u53e6\u5916\uff0c\u4f4d\u7f6e\u504f\u501a\u53ef\u88ab\u89c6\u4e3a\u8fdd\u53cd SUTVA(a)\u3002\u4f8b\u5982\uff0c\u5728\u70b9\u51fb\u7387\u9884\u6d4b\u4efb\u52a1\u4e2d\uff0c\u5047\u8bbe\u4e00\u4e2a\u5355\u5143\u662f\u4e00\u5bf9\u7528\u6237\u548c\u7269\u54c1\u3002\u5982\u679c\u7269\u54c1 i \u5411\u7528\u6237 u  \u66dd\u5149\uff0c\u5219\u5c06 Yu, i<\/sub><\/span>(1) \u5b9a\u4e49\u4e3a\u5355\u51fb\u884c\u4e3a\u3002\u8fd9\u65f6\uff0cYu, i<\/sub><\/span>(1) \u5c06\u53d6\u51b3\u4e8e\u66b4\u9732\u7684\u4f4d\u7f6e\uff0c\u5e76\u4e14\u4f1a\u51fa\u73b0\u591a\u79cd\u5904\u7406\u65b9\u6848\u3002\u5bf9\u4e8e\u4f4d\u7f6e\u504f\u501a\uff0c\u6211\u4eec\u53ef\u4ee5\u8003\u8651\u4f5c\u4e3a\u5904\u7406\u7684\u4f4d\u7f6e\uff0c\u7136\u540e\u5b83\u53ef\u4ee5\u88ab\u89c6\u4e3a\u591a\u503c\u5904\u7406\u7684\u95ee\u9898\u3002\u66dd\u5149\u504f\u501a\u5dee\u6e90\u4e8e\u7528\u6237\u53ea\u63a5\u89e6\u7279\u5b9a\u7269\u54c1\u4e2d\u7684\u4e00\u90e8\u5206\u3002\u4e5f\u5c31\u662f\u8bf4\uff0c\u4e00\u4e9b\u7528\u6237\u4ee5\u96f6\u6982\u7387\u63a5\u89e6\u67d0\u4e9b\u7269\u54c1\u3002\u56e0\u6b64\uff0c\u66dd\u5149\u504f\u501a\u53ef\u89c6\u4e3a\u8fdd\u53cd\u6b63\u6027\u5047\u8bbe\u3002<\/span><\/section>\n

    <\/section>\n

    <\/section>\n

    \n
    \n
    \n
    \n
    \n

    <\/section>\n

    <\/section>\n
    \n
    <\/svg><\/section>\n<\/section>\n<\/section>\n
    \n

    4. \u56e0\u679c\u516c\u5f00\u7814\u7a76\u95ee\u9898<\/strong><\/strong><\/p>\n<\/section>\n

    \n

    <\/section>\n

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


    <\/p>\n

    \u6700\u8fd1\uff0c\u8d8a\u6765\u8d8a\u591a\u7684 RS \u7814\u7a76\u8005\u8bd5\u56fe\u5e94\u7528\u56e0\u679c\u63a8\u7406\u65b9\u6cd5\u6765\u5904\u7406 RS \u4efb\u52a1\uff0c\u5982 CTR\/CVR \u9884\u6d4b\u3001\u5ef6\u8fdf\u53cd\u9988\u7b49\uff0c\u5c3d\u7ba1\u5982\u6b64\uff0c\u4ecd\u7136\u5b58\u5728\u8bb8\u591a\u6311\u6218\u548c\u673a\u4f1a\u3002\u901a\u8fc7\u5c06\u73b0\u6709\u7684\u7814\u7a76\u4e0e\u4e0a\u9762\u8ba8\u8bba\u7684\u56e0\u679c\u5206\u6790\u6846\u67b6<\/span>\u76f8\u5339\u914d\uff0c\u6211\u4eec\u53d1\u73b0\u4e86\u4ee5\u4e0b\u7684\u516c\u5f00\u7814\u7a76\u65b9\u5411\uff0c\u8fd9\u4e9b\u65b9\u5411\u5728 RS \u8fdb\u884c\u7814\u7a76\u7684\u6f5c\u5728\u7ed3\u679c\u6846\u67b6\u4e2d\u5f88\u5c11\u88ab\u6b63\u5f0f\u5f62\u5f0f\u5316\u3002<\/span><\/section>\n

    <\/section>\n

    4.1 \u6570\u636e\u878d\u5408 (Data Fusion)<\/span><\/strong><\/span><\/h2>\n


    <\/span><\/p>\n

    \u4e00\u4e2a\u5178\u578b\u7684\u60c5\u51b5\u662f\u5c06\u5927\u91cf\u6709\u504f\u7684<\/span>\uff08\u89c2\u5bdf\u6027\u6216\u975e\u5747\u5300\u6027\uff09<\/span>\u6570\u636e\u96c6\u548c\u5c11\u91cf\u65e0\u504f\u7684<\/span>\uff08\u5b9e\u9a8c\u6027\u6216\u5747\u5300\u6027\uff09<\/span>\u6570\u636e\u96c6\u7ed3\u5408\u8d77\u6765\u3002\u6709\u504f\u7684\u6570\u636e\u548c\u65e0\u504f\u7684\u6570\u636e\u5177\u6709\u4e92\u8865\u7684\u7279\u70b9\u3002\u6709\u504f\u7684\u6570\u636e\u4e0d\u53ef\u907f\u514d\u5730\u53d7\u5230\u9690\u85cf\/\u672a\u6d4b\u91cf\u7684\u6df7\u6742\u56e0\u7d20\u7684\u5f71\u54cd\uff0c\u5373\u4f7f\u6837\u672c\u91cf\u4e3a\u65e0\u7a77\u5927\uff0c\u4e5f\u4f1a\u626d\u66f2\u56e0\u679c\u5173\u7cfb\u7684\u7ed3\u8bba\u3002<\/span><\/section>\n

    <\/span><\/section>\n
    \u76f8\u6bd4\u4e4b\u4e0b\uff0c\u901a\u8fc7\u7cbe\u5fc3\u8bbe\u8ba1\u7684\u5b9e\u9a8c\u6536\u96c6\u7684\u65e0\u504f\u6570\u636e\u6ca1\u6709<\/span>\uff08\u9690\u85cf\u7684\uff09<\/span>\u6df7\u6742\u504f\u501a\uff0c\u5b83\u4e3a\u8bc4\u4f30\u53bb\u504f\u65b9\u6cd5\u63d0\u4f9b\u4e86\u9ec4\u91d1\u6807\u51c6\u3002\u603b\u4e4b\uff0c\u6570\u636e\u878d\u5408\u662f\u63d0\u9ad8 RS \u8d28\u91cf\u7684\u4e00\u4e2a\u6709\u5e0c\u671b\u7684\u7b56\u7565\u3002<\/span><\/section>\n

    <\/span><\/section>\n

    4.2 \u5e8f\u5217\u63a8\u8350 (Sequential Recommendation)<\/span><\/strong><\/span><\/h2>\n


    <\/span><\/p>\n

    \u901a\u8fc7\u5bf9\u7528\u6237\u884c\u4e3a\u5e8f\u5217\u7684\u5efa\u6a21\uff0c\u5982\u8d2d\u4e70\u5546\u54c1\u7684\u5e8f\u5217\uff0cRS \u53ef\u4ee5\u5b66\u4e60\u7528\u6237\u5174\u8da3\u7684\u53d8\u5316\u5e76\u9884\u6d4b\u7528\u6237\u7684\u4e0b\u4e00\u6b65\u884c\u4e3a\u3002\u4ece\u56e0\u679c\u5173\u7cfb\u7684\u89d2\u5ea6\u770b\uff0c\u53ef\u4ee5\u8ba4\u4e3a RS \u7684\u5206\u914d\u673a\u5236\u548c\u6f5c\u5728\u7ed3\u679c\u662f\u968f\u7740\u65f6\u95f4\u5e8f\u5217\u7684\u53d8\u5316\u800c\u53d8\u5316\u7684\uff0c\u5176\u76ee\u7684\u662f\u52a8\u6001\u5730\u6355\u6349\u7528\u6237\u5174\u8da3\u7684\u53d8\u5316\uff0c\u4ece\u800c\u5b9e\u73b0\u66f4\u51c6\u786e\u7684\u63a8\u8350\u3002<\/span><\/section>\n

    <\/section>\n

    4.3 \u63a8\u8350\u7cfb\u7edf\u516c\u5e73\u6027 (Fairness in RS)<\/span><\/strong><\/span><\/h2>\n


    <\/span><\/p>\n

    \u8bb8\u591a\u6587\u732e\u901a\u8fc7\u53cd\u4e8b\u5b9e\u7684\u56e0\u679c\u5173\u7cfb\u6765\u5b9a\u4e49\u7fa4\u4f53\u516c\u5e73\u548c\u4e2a\u4eba\u516c\u5e73\u3002\u7136\u800c\uff0c\u5982\u4f55\u5728RS\u4e2d\u7528\u56e0\u679c\u6846\u67b6\u6765\u6b63\u5f0f\u5b9a\u4e49\u516c\u5e73\u6027\u4ecd\u7136\u662f\u6a21\u7cca\u7684\uff0c\u7279\u522b\u662f\u5f53\u7528\u6237\u6709\u793e\u4ea4\u7f51\u7edc\u65f6\uff0c\u4f1a\u8fdd\u53cdSUTVA(b)\uff0c\u7ed9\u56e0\u679c\u516c\u5e73\u6027\u7684\u826f\u5b9a\u6027\u5e26\u6765\u66f4\u5927\u6311\u6218\u3002\u6b64\u5916\uff0c\u5982\u4f55\u4fee\u6539\u4f20\u7edf\u7684\u56e0\u679c\u63a8\u8350\u6a21\u578b\u4ee5\u5b9e\u73b0\u51c6\u786e\u6027\u548c\u516c\u5e73\u6027\u7684\u5e73\u8861\uff0c\u4ecd\u6709\u5f88\u5927\u7684\u7814\u7a76\u7a7a\u95f4\u3002<\/span><\/section>\n

    <\/section>\n

    4.4 \u4ea4\u4e92\u884c\u4e3a (Interference)<\/span><\/strong><\/span><\/h2>\n


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    \u5c3d\u7ba1\u51e0\u4e4e\u6240\u6709\u5173\u4e8e\u56e0\u679c\u5173\u7cfb\u542f\u53d1\u5efa\u8bae\u7684\u6587\u7ae0\u90fd\u9ed8\u8ba4\u4e86 SUTVA \u5047\u8bbe\uff0c\u4f46\u6b63\u5982\u524d\u6587\u6240\u8ba8\u8bba\u7684\uff0c SUTVA \u5047\u8bbe\u5728\u5f88\u591a\u60c5\u51b5\u4e0b\u4f1a\u88ab\u8fdd\u53cd\uff0c\u4ece\u800c\u5bfc\u81f4\u6709\u504f\u7684\u4f30\u8ba1\u3002\u53e6\u4e00\u79cd\u5f62\u5f0f\u7684\u5e72\u6270\u662f\u5728\u4e0d\u540c\u5355\u4f4d\u7684\u6f5c\u5728\u7ed3\u679c\u4e4b\u95f4\u3002\u4f8b\u5982\uff0c\u4e00\u4e2a\u7528\u6237\u7684\u8d2d\u4e70\u884c\u4e3a\u4f1a\u5f71\u54cd\u4ed6\u793e\u4ea4\u7f51\u7edc\u4e2d\u5176\u4ed6\u7528\u6237\u7684\u8d2d\u4e70\u884c\u4e3a\uff0c\u8fd9\u5728\u793e\u4ea4\u63a8\u8350\u4e2d\u7ecf\u5e38\u9047\u5230\u3002<\/span><\/section>\n

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

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


    <\/p>\n

    \u56e0\u679c\u5173\u7cfb\u4e3a RS \u4e2d\u53bb\u504f\u548c\u9884\u6d4b\u4efb\u52a1\u7684\u7b97\u6cd5\u63d0\u4f9b\u4e86\u65b0\u7684\u673a\u4f1a\uff0c\u4f7f\u76f8\u5173\u7b97\u6cd5\u5177\u6709\u66f4\u51fa\u8272\u7684\u6027\u80fd\u3002\u672c\u6587\u901a\u8fc7\u4e3a RS \u63d0\u4f9b\u4e00\u4e2a\u7edf\u4e00\u7684\u56e0\u679c\u5206\u6790\u6846\u67b6\u6765\u56de\u987e\u76f8\u5173\u7814\u7a76\uff0c\u63ed\u793a\u5e76\u8be6\u7ec6\u8ba8\u8bba\u4e86\u4e00\u76f4\u88ab\u5ffd\u89c6\u4f46\u540c\u6837\u91cd\u8981\u7684\u56e0\u679c\u5047\u8bbe\u7684\u6709\u6548\u6027\u3002\u4ece\u8fdd\u53cd\u56e0\u679c\u5047\u8bbe\u7684\u89d2\u5ea6\u5bf9 RS \u4e2d\u7684\u5404\u79cd\u504f\u501a\u8fdb\u884c\u4e86\u65b0\u7684\u89e3\u91ca\u3002\u6240\u63d0\u51fa\u7684 RS \u56e0\u679c\u5206\u6790\u6846\u67b6\u88ab\u5e94\u7528\u4e8e\u4e25\u8c28\u5730\u5f62\u5f0f\u5316\u5927\u91cf\u7684 RS \u4efb\u52a1\uff0c\u5982\u975e\u4f9d\u4ece\u95ee\u9898\u3001\u4ea4\u4e92\u504f\u501a\u548c\u7b56\u7565\u5b66\u4e60\u3002<\/span><\/section>\n

    <\/span><\/section>\n
    \u672c\u6587\u6700\u540e\u6982\u8ff0\u4e86\u56e0\u679c\u4f30\u8ba1\u65b9\u6cd5\uff0c\u5e0c\u671b\u80fd\u5728\u56e0\u679c\u63a8\u8350\u9886\u57df\u63d0\u4f9b\u65b0\u7684\u7814\u7a76\u673a\u4f1a\uff0c\u5305\u62ec\u4f46\u4e0d\u9650\u4e8e\u53bb\u504f\u548c\u9884\u6d4b\u4efb\u52a1\u3002\u6b64\u5916\uff0c\u6709\u671b\u5f00\u53d1\u51fa\u5177\u6709\u5f31\u5316\u6216\u66ff\u4ee3 RS \u7814\u7a76\u4e2d\u5e38\u89c1\u5047\u8bbe\u7684\u65b0\u65b9\u6cd5\u3002<\/span><\/section>\n

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    \u53c2\u8003\u6587\u732e<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n

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    <\/p>\n

      \n
    1. \n
      Elias Bareinboim, Jin Tian, and Judea Pearl. Recovering from selection bias in causal and statistical inference. In AAAI, 2014.<\/section>\n<\/li>\n
    2. \n
      Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, and Keping Yang. Autodebias: Learning to debias for recommendation. In SIGIR, 2021.<\/section>\n<\/li>\n
    3. \n
      Jiawei Chen, Hande Dong, Xiang   Wang,   Fuli   Feng,   Meng   Wang,   and   Xiangnan He. Bias and debias in recommender system: A survey and future directions. https:\/\/arxiv.org\/abs\/2010.03240v1, 2020.<\/section>\n<\/li>\n
    4. \n
      Juan D. Correa, Jin Tian, and Elias Bareinboim. Identification of causal effect in the presence of selection bias. In AAAI, 2019.<\/section>\n<\/li>\n
    5. \n
      Prem Gopalan, Jake M. Hofman, and David M. Blei. Scalable recommendation with hierar- chical poisson factorization. In UAI, 2015.<\/section>\n<\/li>\n
    6. \n
      Tiankai Gu, Kun Kuang, Hong Zhu, Jingjie Li, Zhenhua Dong, Wenjie Hu, Zhenguo Li, Xiuqiang He, and Yue Liu. Estimating true post-click conversion via group-stratified coun- terfactual inference. In ADKDD, 2021.<\/section>\n<\/li>\n
    7. \n
      Siyuan Guo, Lixin Zou, Yiding Liu, Wenwen Ye, Suqi Cheng, Shuaiqiang Wang, Hechang Chen, Dawei Yin, and Yi Chang. Enhanced doubly robust learning for debiasing post-click conversion rate estimation. In SIGIR \u201921: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event, Canada, July 11-15, 2021, pages 275\u2013284. ACM, 2021.<\/section>\n<\/li>\n
    8. \n
      Miguel A. Hern\u00e1n and James M. Robins. Causal Inference: What If. Boca Raton: Chapman and Hall\/CRC, 2020.<\/section>\n<\/li>\n
    9. \n
      Nathan Kallus. More e\ufb00icient policy learning via optimal retargeting. Journal of the American Statistical Association, 116:646\u2013658, 2021.<\/section>\n<\/li>\n
    10. \n
      Dawen Liang, Laurent Charlin, and David M. Blei. Causal inference for recommender systems. In RecSys, 2020.<\/section>\n<\/li>\n
    11. \n
      Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, and Ed H Chi. Modeling task relationships in multi-task learning with multi-gate mixture-of experts. In KDD.<\/section>\n<\/li>\n
    12. \n
      Xiao Ma, Liqin Zhao, Guan Huang, Zhi Wang, Zelin Hu, Xiaoqiang Zhu, and Kun Gai. Entire space multi-task model: An effective approach for estimating post-click conversion rate. In SIGIR, page 1137\u20131140, 2018.<\/section>\n<\/li>\n
    13. \n
      Yuta Saito, Suguru Yaginuma, Yuta Nishino, Hayato Sakata, and Kazuhide Nakata. Unbiased recommender learning from missing-not-at-random implicit feedback. In James Caverlee, Xia (Ben) Hu, Mounia Lalmas, and Wei Wang, editors, WSDM \u201920: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020, pages 501\u2013509. ACM, 2020.<\/section>\n<\/li>\n
    14. \n
      Tobias Schnabel, Adith Swaminathan, Ashudeep Singh, Navin Chandak, and Thorsten Joachims. Recommendations as treatments: Debiasing learning and evaluation. In ICML, 2016.<\/section>\n<\/li>\n
    15. \n
      Bo-Wen Yuan, Jui-Yang Hsia, Meng-Yuan Yang, Hong Zhu, Chih-Yao Chang, Zhenhua Dong, and Chih-Jen Lin. Improving ad click prediction by considering non-displayed events. In Proceedings of the 28th ACM International Conference on Information and Knowledge Man- agement, CIKM 2019, Beijing, China, November 3-7, 2019, pages 329\u2013338. ACM, 2019.<\/section>\n<\/li>\n
    16. \n
      Bowen Yuan, Yaxu Liu, Jui-Yang Hsia, Zhenhua Dong, and Chih-Jen Lin.   Unbiased ad click prediction for position-aware advertising systems. In Fourteenth ACM Conference on Recommender Systems, pages 368\u2013377, 2020.<\/section>\n<\/li>\n
    17. \n
      Wenhao Zhang, Wentian Bao, Xiao-Yang Liu, Keping Yang, Quan Lin, Hong Wen, and Ramin Ramezani. Large-scale causal approaches to debiasing post-click conversion rate estimation with multi-task learning. In WWW, 2020.<\/section>\n<\/li>\n<\/ol>\n


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      \uff08\u53c2\u8003\u6587\u732e\u53ef\u4e0a\u4e0b\u6ed1\u52a8<\/strong>\u67e5\u770b\uff09<\/p>\n<\/section>\n<\/section>\n


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      \u56e0\u679c\u79d1\u5b66\u8bfb\u4e66\u4f1a\u7b2c\u4e09\u5b63\u542f\u52a8<\/strong><\/p>\n<\/section>\n<\/section>\n<\/section>\n<\/section>\n


      <\/p>\n

      \u7531\u667a\u6e90\u793e\u533a\u3001\u96c6\u667a\u4ff1\u4e50\u90e8\u8054\u5408\u4e3e\u529e\u7684\u56e0\u679c\u79d1\u5b66\u4e0eCausal AI\u8bfb\u4e66\u4f1a\u7b2c\u4e09\u5b63<\/a>\uff0c\u5c06\u4e3b\u8981\u9762\u5411\u4e24\u7c7b\u4eba\u7fa4\uff1a\u5982\u679c\u4f60\u4ece\u4e8b\u8ba1\u7b97\u673a\u76f8\u5173\u65b9\u5411\u7814\u7a76\uff0c\u5e0c\u671b\u4e3a\u4e0d\u540c\u9886\u57df\u5f15\u5165\u65b0\u7684\u8ba1\u7b97\u65b9\u6cd5\uff0c\u901a\u8fc7\u5927\u6570\u636e\u3001\u65b0\u7b97\u6cd5\u5f97\u5230\u65b0\u6210\u679c\uff0c\u53ef\u4ee5\u901a\u8fc7\u8bfb\u4e66\u4f1a\u5404\u4e2a\u9886\u57df\u7684\u6838\u5fc3\u56e0\u679c\u95ee\u9898\u4ecb\u7ecd\u548c\u8bba\u6587\u63a8\u8350\u5feb\u901f\u5165\u624b\uff1b\u5982\u679c\u4f60\u4ece\u4e8b\u5176\u4ed6\u7406\u5de5\u79d1\u6216\u4eba\u6587\u793e\u79d1\u9886\u57df\u7814\u7a76\uff0c\u4e5f\u53ef\u4ee5\u901a\u8fc7\u6240\u5c5e\u9886\u57df\u7684\u56e0\u679c\u7814\u7a76\u7efc\u8ff0\u4ecb\u7ecd\u548c\u7814\u8ba8\u5df2\u6709\u5de5\u4f5c\u7684\u793a\u4f8b\u4ee3\u7801\uff0c\u5728\u81ea\u5df1\u7684\u7814\u7a76\u4e2d\u5feb\u901f\u5f00\u59cb\u5c1d\u8bd5\u90e8\u7f72\u7ed3\u5408\u56e0\u679c\u7684\u7b97\u6cd5\u3002\u8bfb\u4e66\u81ea2021\u5e7410\u670824\u65e5\u5f00\u59cb\uff0c\u6bcf\u5468\u65e5\u4e0a\u5348 10:00-12:00\u4e3e\u529e\uff0c\u6301\u7eed\u65f6\u95f4\u9884\u8ba1 2-3 \u4e2a\u6708\u3002<\/span><\/p>\n


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      \u8be6\u60c5\u8bf7\u89c1\uff1a<\/span><\/p>\n

      \u56e0\u679c+X\uff1a\u89e3\u51b3\u591a\u5b66\u79d1\u9886\u57df\u7684\u56e0\u679c\u95ee\u9898 | \u56e0\u679c\u79d1\u5b66\u8bfb\u4e66\u4f1a\u7b2c\u4e09\u5b63\u542f\u52a8<\/a><\/span><\/strong><\/span><\/p>\n

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