{"id":105151,"date":"2026-09-15T00:16:20","date_gmt":"2026-09-14T16:16:20","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/105151.html"},"modified":"2026-09-15T00:16:20","modified_gmt":"2026-09-14T16:16:20","slug":"transe-%e4%b8%80%e4%b8%aa%e5%90%91%e9%87%8f%e7%ad%89%e5%bc%8f%ef%bc%8c%e8%ae%a9%e7%9f%a5%e8%af%86%e5%9b%be%e8%b0%b1%e5%ad%a6%e4%bc%9a%e6%8e%a8%e7%90%86","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/105151.html","title":{"rendered":"TransE \u4e00\u4e2a\u5411\u91cf\u7b49\u5f0f\uff0c\u8ba9\u77e5\u8bc6\u56fe\u8c31\u5b66\u4f1a\u63a8\u7406"},"content":{"rendered":"

TransE \u4e00\u4e2a\u5411\u91cf\u7b49\u5f0f，\u8ba9\u77e5\u8bc6\u56fe\u8c31\u5b66\u4f1a\u63a8\u7406<\/h2>\n

\u4e00\u53e5\u8bdd\u5bfc\u8bed：\u628a\u5173\u7cfb\u5f53\u6210\u4e00\u6b21\u5e73\u79fb，\u201c\u5934\u5b9e\u4f53 + \u5173\u7cfb \u2248 \u5c3e\u5b9e\u4f53\u201d，\u77e5\u8bc6\u56fe\u8c31\u5c31\u80fd\u5728\u5411\u91cf\u7a7a\u95f4\u91cc\u505a\u63a8\u7406\u2014\u2014\u4f46\u5b83\u683d\u5728\u4e86\u591a\u5bf9\u4e00\u5173\u7cfb\u4e0a\u3002<\/p>\n

\u4e00\u3001\u80cc\u666f\u4e0e\u75db\u70b9<\/h3>\n

\u77e5\u8bc6\u56fe\u8c31\u91cc\u5b58\u7684\u662f"\u5f20\u4e09\u2014\u5c31\u804c\u4e8e\u2014\u67d0\u516c\u53f8""\u5317\u4eac\u2014\u4f4d\u4e8e\u2014\u534e\u5317"\u8fd9\u6837\u7684\u4e09\u5143\u7ec4\u4e8b\u5b9e\u3002\u53ef\u771f\u5b9e\u56fe\u8c31\u6c38\u8fdc\u662f\u4e0d\u5b8c\u6574\u7684：\u5927\u91cf\u5173\u7cfb\u7f3a\u5931，\u9700\u8981\u6211\u4eec\u6839\u636e\u5df2\u6709\u4e8b\u5b9e\u53bb\u63a8\u65ad\u90a3\u6761\u7f3a\u5931\u7684\u8fb9，\u4e5f\u5c31\u662f\u94fe\u63a5\u9884\u6d4b\u3002\u65e9\u671f\u505a\u6cd5\u662f\u7eaf\u7b26\u53f7\u903b\u8f91，\u89c4\u5219\u5199\u4e0d\u5b8c\u3001\u6cdb\u5316\u53c8\u5dee\u30022013 \u5e74 TransE \u7528\u4e00\u53e5\u8bdd\u2014\u2014\u5173\u7cfb\u5373\u5e73\u79fb\u2014\u2014\u628a\u8fde\u7eed\u7a7a\u95f4\u7684\u5e73\u6ed1\u6027\u5e26\u8fdb\u4e86\u79bb\u6563\u4e8b\u5b9e，\u6b64\u540e\u6570\u5e74\u90fd\u662f\u57fa\u51c6\u7ebf\u4e0a\u7684\u5e38\u5ba2\u3002<\/p>\n

\u95ee\u9898\u51fa\u5728\u5173\u7cfb\u53d8\u590d\u6742\u4e4b\u540e\u3002\u8bbe\u60f3\u4e00\u5bb6\u516c\u53f8\u91cc\u6240\u6709\u4eba\u7684\u5173\u7cfb："\u5c31\u804c\u4e8e"\u628a\u4e0a\u5343\u4e2a\u5458\u5de5\u6307\u5411\u540c\u4e00\u4e2a\u516c\u53f8，\u8fd9\u662f\u591a\u5bf9\u4e00；\u53cd\u8fc7\u6765，\u4e00\u4f4d\u7ecf\u7406\u624b\u4e0b\u7ba1\u7740\u4e00\u4e2a\u56e2\u961f，\u8fd9\u662f\u4e00\u5bf9\u591a\u3002TransE \u5728\u8fd9\u4e9b\u60c5\u5f62\u4e0b\u4f1a\u9732\u51fa\u7834\u7efd\u2014\u2014\u5b83\u8981\u6c42\u6240\u6709"\u5c31\u804c\u4e8e\u540c\u4e00\u5bb6\u516c\u53f8"\u7684\u5458\u5de5\u6ee1\u8db3 eh\u2248e\u516c\u53f8\u2212r\u5c31\u804c\u4e8e\\\\mathbf e_h \\\\approx \\\\mathbf e_{\\\\text{\u516c\u53f8}} – \\\\mathbf r_{\\\\text{\u5c31\u804c\u4e8e}}<\/span><\/span>e<\/span><\/span>h<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>e<\/span><\/span>\u516c\u53f8<\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2212<\/span><\/span><\/span><\/span>r<\/span><\/span>\u5c31\u804c\u4e8e<\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>，\u7b49\u5f0f\u53f3\u8fb9\u662f\u540c\u4e00\u4e2a\u5411\u91cf，\u4e8e\u662f\u8fd9\u4e9b\u5458\u5de5\u5728\u5d4c\u5165\u7a7a\u95f4\u91cc\u88ab\u786c\u751f\u751f\u6324\u6210\u4e00\u56e2\u3002\u4ed6\u4eec\u672c\u6765\u5404\u6709\u5404\u7684\u5c97\u4f4d\u3001\u5404\u6709\u5404\u7684\u5de5\u9f84，\u5374\u88ab\u6a21\u578b\u62b9\u5e73\u6210\u4e86\u540c\u4e00\u4e2a\u70b9\u3002\u8fd9\u4e0d\u662f\u8bad\u7ec3\u4e0d\u591f，\u800c\u662f\u6a21\u578b\u5047\u8bbe\u672c\u8eab\u5bfc\u81f4\u7684\u51e0\u4f55\u9000\u5316\u3002<\/p>\n

\u4e8c\u3001\u6838\u5fc3\u539f\u7406<\/h3>\n

1. \u628a TransE \u7684\u5931\u8d25\u7b97\u6e05\u695a<\/h4>\n

\u5148\u660e\u786e TransE \u7684\u6253\u5206：<\/p>\n

d(h,r,t)=\u2225eh+rr\u2212et\u2225.d(h,r,t)=\\\\big\\\\|\\\\mathbf e_h+\\\\mathbf r_r-\\\\mathbf e_t\\\\big\\\\|.<\/span><\/span>d<\/span>(<\/span>h<\/span>,<\/span><\/span>r<\/span>,<\/span><\/span>t<\/span>)<\/span><\/span>=<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>e<\/span><\/span>h<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>+<\/span><\/span><\/span><\/span>r<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2212<\/span><\/span><\/span><\/span>e<\/span><\/span>t<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>.<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

\u8bad\u7ec3\u65f6\u5b9e\u4f53\u5411\u91cf\u88ab\u5f52\u4e00\u5316\u5230\u5355\u4f4d\u7403\u9762\u3002\u8003\u8651\u4e00\u4e2a\u5178\u578b\u7684\u591a\u5bf9\u4e00\u5173\u7cfb rr<\/span><\/span>r<\/span><\/span><\/span><\/span><\/span>：\u8bb8\u591a\u5934\u5b9e\u4f53 h1,h2,\u2026,hkh_1,h_2,\\\\dots,h_k<\/span><\/span>h<\/span><\/span>1<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span><\/span>h<\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span><\/span>\u2026<\/span><\/span>,<\/span><\/span>h<\/span><\/span>k<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span> \u90fd\u901a\u8fc7 rr<\/span><\/span>r<\/span><\/span><\/span><\/span><\/span> \u6307\u5411\u540c\u4e00\u4e2a\u5c3e\u5b9e\u4f53 tt<\/span><\/span>t<\/span><\/span><\/span><\/span><\/span>\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\u6bcf\u6761\u4e09\u5143\u7ec4\u90fd\u5e94\u6ee1\u8db3 ehi+rr\u2248et\\\\mathbf e_{h_i} + \\\\mathbf r_r \\\\approx \\\\mathbf e_t<\/span><\/span>e<\/span><\/span>h<\/span><\/span>i<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>+<\/span><\/span><\/span><\/span>r<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>e<\/span><\/span>t<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>，\u4e8e\u662f<\/p>\n

eh1\u2248eh2\u2248\u22ef\u2248ehk\u2248et\u2212rr.\\\\mathbf e_{h_1}\\\\approx\\\\mathbf e_{h_2}\\\\approx\\\\cdots\\\\approx\\\\mathbf e_{h_k}\\\\approx \\\\mathbf e_t-\\\\mathbf r_r .<\/span><\/span>e<\/span><\/span>h<\/span><\/span>1<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>e<\/span><\/span>h<\/span><\/span>2<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>\u22ef<\/span><\/span>\u2248<\/span><\/span><\/span><\/span>e<\/span><\/span>h<\/span><\/span>k<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2248<\/span><\/span><\/span><\/span>e<\/span><\/span>t<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2212<\/span><\/span><\/span><\/span>r<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>.<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

\u4e5f\u5c31\u662f\u8bf4，\u6240\u6709\u6307\u5411\u540c\u4e00\u76ee\u6807\u7684\u5934\u5b9e\u4f53\u88ab\u8feb\u5171\u4eab\u540c\u4e00\u4e2a\u5d4c\u5165，\u5dee\u5f02\u88ab\u5b8c\u5168\u62b9\u6389\u3002\u8fd9\u4e0d\u662f\u8bad\u7ec3\u4e0d\u8db3，\u800c\u662f\u6a21\u578b\u5047\u8bbe\u9020\u6210\u7684\u51e0\u4f55\u9000\u5316\u3002\u540c\u7406，\u4e00\u5bf9\u591a\u5173\u7cfb\u4f1a\u8ba9\u6240\u6709\u5c3e\u5b9e\u4f53\u6324\u6210\u4e00\u56e2\u3002<\/p>\n

2. TransH：\u628a\u5b9e\u4f53\u6295\u5f71\u5230\u5173\u7cfb\u8d85\u5e73\u9762<\/h4>\n

TransH \u7684\u4fee\u6cd5\u662f：\u4e0d\u518d\u76f4\u63a5\u6bd4\u8f83\u5b9e\u4f53\u5411\u91cf，\u800c\u662f\u5148\u628a\u5b83\u4eec\u6295\u5f71\u5230\u4e00\u5f20\u7531\u5173\u7cfb\u51b3\u5b9a\u7684\u8d85\u5e73\u9762\u4e0a\u3002\u8bbe\u5173\u7cfb rr<\/span><\/span>r<\/span><\/span><\/span><\/span><\/span> \u5bf9\u5e94\u4e00\u4e2a\u5355\u4f4d\u6cd5\u5411\u91cf wr\\\\mathbf w_r<\/span><\/span>w<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>，\u5b9e\u4f53 e\\\\mathbf e<\/span><\/span>e<\/span><\/span><\/span><\/span><\/span> \u5728\u5176\u4e0a\u7684\u6295\u5f71\u4e3a<\/p>\n

e\u22a5=e\u2212(wr\u22a4e)wr.\\\\mathbf e_{\\\\perp}=\\\\mathbf e-\\\\big(\\\\mathbf w_r^{\\\\top}\\\\mathbf e\\\\big)\\\\mathbf w_r .<\/span><\/span>e<\/span><\/span>\u22a5<\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>e<\/span><\/span>\u2212<\/span><\/span><\/span><\/span>(<\/span><\/span>w<\/span><\/span>r<\/span><\/span><\/span><\/span>\u22a4<\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>e<\/span>)<\/span><\/span>w<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>.<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

\u6253\u5206\u53d8\u6210 d(h,r,t)=\u2225eh\u22a5+rr\u2212et\u22a5\u2225d(h,r,t)=\\\\big\\\\|\\\\mathbf e_{h\\\\perp}+\\\\mathbf r_r-\\\\mathbf e_{t\\\\perp}\\\\big\\\\|<\/span><\/span>d<\/span>(<\/span>h<\/span>,<\/span><\/span>r<\/span>,<\/span><\/span>t<\/span>)<\/span><\/span>=<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>e<\/span><\/span>h<\/span>\u22a5<\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>+<\/span><\/span><\/span><\/span>r<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2212<\/span><\/span><\/span><\/span>e<\/span><\/span>t<\/span>\u22a5<\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u3002\u5999\u5904\u5728\u4e8e：\u540c\u4e00\u4e2a\u5b9e\u4f53\u5728\u4e0d\u540c\u5173\u7cfb\u4e0b\u4f1a\u88ab\u6295\u5f71\u5230\u4e0d\u540c\u7684\u8d85\u5e73\u9762\u4e0a，\u5f97\u5230\u4e0d\u540c\u7684"\u50cf"\u3002\u5458\u5de5\u5f20\u4e09\u5728"\u5c31\u804c\u4e8e"\u8fd9\u5f20\u5e73\u9762\u4e0a\u53ef\u4ee5\u548c\u540c\u4e8b\u91cd\u5408，\u4f46\u5728"\u64c5\u957f"\u90a3\u5f20\u5e73\u9762\u4e0a\u53c8\u80fd\u548c\u522b\u4eba\u533a\u5206\u5f00，\u4e00\u5200\u5207\u53d8\u6210\u4e86\u5206\u60c5\u51b5\u8ba8\u8bba\u3002<\/p>\n

3. TransR：\u5b9e\u4f53\u7a7a\u95f4\u4e0e\u5173\u7cfb\u7a7a\u95f4\u5206\u79bb<\/h4>\n

TransH \u7528\u7684\u662f\u4e00\u5f20\u5e73\u9762，\u8868\u8fbe\u529b\u4ecd\u7136\u6709\u9650\u3002TransR \u5e72\u8106\u4e3a\u6bcf\u4e2a\u5173\u7cfb rr<\/span><\/span>r<\/span><\/span><\/span><\/span><\/span> \u5b66\u4e00\u4e2a\u6295\u5f71\u77e9\u9635 Mr\u2208Rd\u00d7k\\\\mathbf M_r\\\\in\\\\mathbb R^{d\\\\times k}<\/span><\/span>M<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2208<\/span><\/span><\/span><\/span>R<\/span><\/span>d<\/span>\u00d7<\/span>k<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>，\u628a kk<\/span><\/span>k<\/span><\/span><\/span><\/span><\/span> \u7ef4\u5b9e\u4f53\u7a7a\u95f4\u7684\u5411\u91cf\u642c\u8fdb dd<\/span><\/span>d<\/span><\/span><\/span><\/span><\/span> \u7ef4\u5173\u7cfb\u7a7a\u95f4：<\/p>\n

ehr=Mreh,etr=Mret.\\\\mathbf e_h^{r}=\\\\mathbf M_r\\\\mathbf e_h,\\\\qquad \\\\mathbf e_t^{r}=\\\\mathbf M_r\\\\mathbf e_t .<\/span><\/span>e<\/span><\/span>h<\/span><\/span><\/span><\/span>r<\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>M<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>e<\/span><\/span>h<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span><\/span><\/span>e<\/span><\/span>t<\/span><\/span><\/span><\/span>r<\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>=<\/span><\/span><\/span><\/span>M<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>e<\/span><\/span>t<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>.<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

\u6253\u5206\u5219\u5728\u5173\u7cfb\u7a7a\u95f4\u91cc\u8fdb\u884c：<\/p>\n

d(h,r,t)=\u2225Mreh+rr\u2212Mret\u2225.d(h,r,t)=\\\\big\\\\|\\\\mathbf M_r\\\\mathbf e_h+\\\\mathbf r_r-\\\\mathbf M_r\\\\mathbf e_t\\\\big\\\\| .<\/span><\/span>d<\/span>(<\/span>h<\/span>,<\/span><\/span>r<\/span>,<\/span><\/span>t<\/span>)<\/span><\/span>=<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>M<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>e<\/span><\/span>h<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>+<\/span><\/span><\/span><\/span>r<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u2212<\/span><\/span><\/span><\/span>M<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>e<\/span><\/span>t<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>.<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

\u8fd9\u4e00\u6b65\u7684\u610f\u4e49\u662f\u5750\u6807\u7cfb\u7684\u4e2a\u6027\u5316：\u5173\u7cfb\u4e0d\u518d\u53ea\u662f\u4e00\u4e2a\u4f4d\u79fb\u65b9\u5411，\u5b83\u8fd8\u5e26\u6765\u4e86\u4e00\u6574\u5957\u4e3a\u81ea\u5df1\u91cf\u8eab\u5b9a\u5236\u7684\u5750\u6807\u53d8\u6362\u3002\u5224\u65ad"\u51fa\u751f\u5730"\u65f6\u6211\u4eec\u5173\u6ce8\u7c4d\u8d2f\u7ef4\u5ea6，\u5224\u65ad"\u64c5\u957f"\u65f6\u5173\u6ce8\u6280\u80fd\u7ef4\u5ea6，\u4e24\u8005\u7684\u5ea6\u91cf\u7a7a\u95f4\u6839\u672c\u4e0d\u540c\u3002\u4ee3\u4ef7\u4e5f\u5f88\u76f4\u63a5：\u6bcf\u4e2a\u5173\u7cfb\u591a\u51fa d\u00d7kd\\\\times k<\/span><\/span>d<\/span><\/span>\u00d7<\/span><\/span><\/span><\/span>k<\/span><\/span><\/span><\/span><\/span> \u4e2a\u53c2\u6570，\u5173\u7cfb\u6570\u4e00\u591a，\u53c2\u6570\u91cf\u5c31\u81a8\u80c0\u3002<\/p>\n

4. \u8bad\u7ec3\u76ee\u6807\u4e0e\u8d1f\u91c7\u6837<\/h4>\n

\u4e09\u79cd\u6a21\u578b\u5171\u7528\u540c\u4e00\u5957\u8fb9\u8ddd\u6392\u5e8f\u635f\u5931：<\/p>\n

L=\u2211(h,r,t)\u2211(h\u2032,r,t\u2032)[\u03b3+d(h,r,t)\u2212d(h\u2032,r,t\u2032)]+.\\\\mathcal L=\\\\sum_{(h,r,t)}\\\\sum_{(h',r,t')}\\\\Big[\\\\gamma+d(h,r,t)-d(h',r,t')\\\\Big]_+ .<\/span><\/span>L<\/span><\/span>=<\/span><\/span><\/span><\/span><\/span>(<\/span>h<\/span>,<\/span>r<\/span>,<\/span>t<\/span>)<\/span><\/span><\/span><\/span><\/span>\u2211<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>(<\/span>h<\/span><\/span>\u2032<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span>r<\/span>,<\/span>t<\/span><\/span>\u2032<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>)<\/span><\/span><\/span><\/span><\/span>\u2211<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>[<\/span><\/span>\u03b3<\/span><\/span>+<\/span><\/span><\/span><\/span>d<\/span>(<\/span>h<\/span>,<\/span><\/span>r<\/span>,<\/span><\/span>t<\/span>)<\/span><\/span>\u2212<\/span><\/span><\/span><\/span>d<\/span>(<\/span>h<\/span><\/span>\u2032<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>,<\/span><\/span>r<\/span>,<\/span><\/span>t<\/span><\/span>\u2032<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>)<\/span>]<\/span><\/span><\/span>+<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span>.<\/span><\/span><\/span><\/span><\/span><\/span><\/p>\n

\u8d1f\u4e09\u5143\u7ec4\u7531\u66ff\u6362\u5934\u6216\u5c3e\u5b9e\u4f53\u5f97\u5230\u3002\u8fd9\u91cc\u6709\u4e00\u4e2a\u5e38\u88ab\u5ffd\u89c6\u7684\u5de5\u7a0b\u7ec6\u8282：\u8d1f\u91c7\u6837\u7684\u5019\u9009\u6c60\u5fc5\u987b\u6309\u5b9e\u4f53\u7c7b\u578b\u9650\u5b9a\u3002\u5bf9"\u4f4d\u4e8e"（\u57ce\u5e02\u2192\u5730\u533a）\u8fd9\u4e2a\u5173\u7cfb，\u628a\u5c3e\u5b9e\u4f53\u66ff\u6362\u6210\u4e00\u4e2a"\u4eba\u7269"，\u9020\u51fa\u6765\u7684\u8d1f\u4f8b\u8fde\u8bed\u6cd5\u90fd\u4e0d\u5408\u6cd5，\u7eaf\u7cb9\u6d6a\u8d39\u68af\u5ea6\u3002<\/p>\n

5. \u8bc4\u6d4b\u534f\u8bae：\u5934\u9884\u6d4b\u6bd4\u5c3e\u9884\u6d4b\u66f4\u80fd\u66b4\u9732\u95ee\u9898<\/h4>\n

\u94fe\u63a5\u9884\u6d4b\u7684\u6807\u51c6\u505a\u6cd5\u662f：\u7ed9\u5b9a (h,r,?)(h,r,?)<\/span><\/span>(<\/span>h<\/span>,<\/span><\/span>r<\/span>,<\/span><\/span>?)<\/span><\/span><\/span><\/span><\/span>，\u7ed9\u6240\u6709\u5019\u9009\u5c3e\u5b9e\u4f53\u6253\u5206\u3001\u6392\u5e8f，\u7edf\u8ba1 Hits@k \u4e0e MRR\u3002\u4f46\u5c3e\u9884\u6d4b\u4f1a\u63a9\u76d6\u591a\u5bf9\u4e00\u5173\u7cfb\u7684\u7f3a\u9677\u2014\u2014\u65e2\u7136\u6240\u6709\u5934\u5b9e\u4f53\u90fd\u6307\u5411\u540c\u4e00\u4e2a\u5c3e，\u53ea\u8981\u6a21\u578b\u5b66\u5230\u4e86\u8fd9\u4e2a\u5c3e\u5b9e\u4f53\u533a\u57df，\u5c3e\u9884\u6d4b\u6210\u7ee9\u7167\u6837\u6f02\u4eae\u3002\u771f\u6b63\u80fd\u6233\u4e2d\u75db\u5904\u7684\u662f\u5934\u9884\u6d4b (?,r,t)(?,r,t)<\/span><\/span>(<\/span>?<\/span>,<\/span><\/span>r<\/span>,<\/span><\/span>t<\/span>)<\/span><\/span><\/span><\/span><\/span>：\u56fa\u5b9a\u5173\u7cfb\u4e0e\u5c3e\u5b9e\u4f53，\u95ee"\u8c01\u662f\u8fd9\u4e2a\u5934"\u3002\u8fd9\u65f6 TransE \u7684\u9000\u5316\u5c31\u66b4\u9732\u4e86，\u51e0\u4e2a\u5408\u6cd5\u5934\u5b9e\u4f53\u5728\u6392\u5e8f\u91cc\u51e0\u4e4e\u6ca1\u6709\u533a\u522b，\u6a21\u578b\u53ea\u80fd\u778e\u731c；\u800c TransR \u56e0\u4e3a\u6709\u5173\u7cfb\u4e13\u5c5e\u5750\u6807\u7cfb，\u4ecd\u80fd\u501f\u52a9\u6295\u5f71\u540e\u7684\u5dee\u5f02\u628a\u5b83\u4eec\u6392\u5f00\u3002<\/p>\n

\u4e09\u3001\u4ee3\u7801\u5b9e\u6218<\/h3>\n

\u4e0b\u9762\u8fd9\u6bb5\u7eaf numpy \u4ee3\u7801\u5728\u540c\u4e00\u5f20\u542b"\u4f4d\u4e8e"\u591a\u5bf9\u4e00\u5173\u7cfb\u7684\u5408\u6210\u77e5\u8bc6\u56fe\u8c31\u4e0a\u8bad\u7ec3 TransE，\u5e76\u7528"\u540c\u5730\u533a\/\u8de8\u5730\u533a\u5e73\u5747\u8ddd\u79bb\u6bd4"\u8fd9\u4e2a\u53ef\u91cf\u5316\u6307\u6807\u68c0\u67e5\u5b83\u662f\u5426\u628a\u540c\u5730\u533a\u57ce\u5e02\u538b\u6241\u4e86：<\/p>\n

import<\/span> numpy as<\/span> np<\/p>\n

rng =<\/span> np.<\/span>random.<\/span>RandomState(<\/span>69<\/span>)<\/span>
\nN_CITY,<\/span> N_REGION,<\/span> N_PERSON,<\/span> DIM,<\/span> GAMMA =<\/span> 12<\/span>,<\/span> 4<\/span>,<\/span> 30<\/span>,<\/span> 20<\/span>,<\/span> 1.0<\/span>
\nC0,<\/span> R0,<\/span> P0 =<\/span> 0<\/span>,<\/span> N_CITY,<\/span> N_CITY +<\/span> N_REGION
\nN_ENT =<\/span> N_CITY +<\/span> N_REGION +<\/span> N_PERSON<\/p>\n

city_region =<\/span> np.<\/span>repeat(<\/span>np.<\/span>arange(<\/span>N_REGION)<\/span>,<\/span> N_CITY \/\/<\/span> N_REGION)<\/span>
\ntriples =<\/span> [<\/span>]<\/span>
\nfor<\/span> c in<\/span> range<\/span>(<\/span>N_CITY)<\/span>:<\/span> # \u4f4d\u4e8e：\u57ce\u5e02 -> \u5730\u533a（\u591a\u5bf9\u4e00）<\/span>
\n triples.<\/span>append(<\/span>(<\/span>C0 +<\/span> c,<\/span> 0<\/span>,<\/span> R0 +<\/span> int<\/span>(<\/span>city_region[<\/span>c]<\/span>)<\/span>)<\/span>)<\/span>
\nfor<\/span> i in<\/span> range<\/span>(<\/span>N_PERSON)<\/span>:<\/span> # \u51fa\u751f\u5730 \/ \u5c45\u4f4f\u5730：\u4eba\u7269 -> \u57ce\u5e02<\/span>
\n home =<\/span> rng.<\/span>randint(<\/span>0<\/span>,<\/span> N_CITY)<\/span>
\n triples.<\/span>append(<\/span>(<\/span>P0 +<\/span> i,<\/span> 1<\/span>,<\/span> C0 +<\/span> home)<\/span>)<\/span>
\n same =<\/span> np.<\/span>where(<\/span>city_region ==<\/span> city_region[<\/span>home]<\/span>)<\/span>[<\/span>0<\/span>]<\/span>
\n triples.<\/span>append(<\/span>(<\/span>P0 +<\/span> i,<\/span> 2<\/span>,<\/span> C0 +<\/span> int<\/span>(<\/span>rng.<\/span>choice(<\/span>same)<\/span>)<\/span>)<\/span>)<\/span>
\nT =<\/span> np.<\/span>array(<\/span>triples)<\/span><\/p>\n

def<\/span> unit<\/span>(<\/span>E)<\/span>:<\/span>
\n return<\/span> E \/<\/span> (<\/span>np.<\/span>linalg.<\/span>norm(<\/span>E,<\/span> axis=<\/span>1<\/span>,<\/span> keepdims=<\/span>True<\/span>)<\/span> +<\/span> 1e-9<\/span>)<\/span><\/p>\n

def<\/span> train_transe<\/span>(<\/span>steps=<\/span>1500<\/span>,<\/span> lr=<\/span>0.05<\/span>,<\/span> bs=<\/span>64<\/span>)<\/span>:<\/span>
\n E =<\/span> unit(<\/span>rng.<\/span>randn(<\/span>N_ENT,<\/span> DIM)<\/span>)<\/span>;<\/span> R =<\/span> rng.<\/span>randn(<\/span>3<\/span>,<\/span> DIM)<\/span> *<\/span> 0.1<\/span>
\n for<\/span> _ in<\/span> range<\/span>(<\/span>steps)<\/span>:<\/span>
\n h,<\/span> r,<\/span> t =<\/span> T[<\/span>rng.<\/span>randint(<\/span>0<\/span>,<\/span> len<\/span>(<\/span>T)<\/span>,<\/span> bs)<\/span>]<\/span>.<\/span>T
\n nt =<\/span> rng.<\/span>randint(<\/span>0<\/span>,<\/span> N_ENT,<\/span> bs)<\/span> # \u7b80\u5316\u8d1f\u91c7\u6837：\u968f\u673a\u66ff\u6362\u5c3e<\/span>
\n vp =<\/span> E[<\/span>h]<\/span> +<\/span> R[<\/span>r]<\/span> –<\/span> E[<\/span>t]<\/span>;<\/span> vn =<\/span> E[<\/span>h]<\/span> +<\/span> R[<\/span>r]<\/span> –<\/span> E[<\/span>nt]<\/span>
\n np_ =<\/span> np.<\/span>linalg.<\/span>norm(<\/span>vp,<\/span> axis=<\/span>1<\/span>)<\/span> +<\/span> 1e-9<\/span>
\n nn_ =<\/span> np.<\/span>linalg.<\/span>norm(<\/span>vn,<\/span> axis=<\/span>1<\/span>)<\/span> +<\/span> 1e-9<\/span>
\n m =<\/span> (<\/span>(<\/span>GAMMA +<\/span> np_ –<\/span> nn_)<\/span> ><\/span> 0<\/span>)<\/span>.<\/span>astype(<\/span>float<\/span>)<\/span> # \u94f0\u94fe：\u53ea\u66f4\u65b0\u8d8a\u754c\u7684\u6837\u672c<\/span>
\n gp =<\/span> (<\/span>m \/<\/span> np_)<\/span>[<\/span>:<\/span>,<\/span> None<\/span>]<\/span> *<\/span> vp
\n gn =<\/span> –<\/span>(<\/span>m \/<\/span> nn_)<\/span>[<\/span>:<\/span>,<\/span> None<\/span>]<\/span> *<\/span> vn
\n gE =<\/span> np.<\/span>zeros_like(<\/span>E)<\/span>;<\/span> gR =<\/span> np.<\/span>zeros_like(<\/span>R)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gE,<\/span> h,<\/span> gp)<\/span>;<\/span> np.<\/span>add.<\/span>at(<\/span>gE,<\/span> t,<\/span> –<\/span>gp)<\/span>;<\/span> np.<\/span>add.<\/span>at(<\/span>gR,<\/span> r,<\/span> gp)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gE,<\/span> h,<\/span> gn)<\/span>;<\/span> np.<\/span>add.<\/span>at(<\/span>gE,<\/span> nt,<\/span> –<\/span>gn)<\/span>;<\/span> np.<\/span>add.<\/span>at(<\/span>gR,<\/span> r,<\/span> gn)<\/span>
\n E =<\/span> unit(<\/span>E –<\/span> lr *<\/span> gE)<\/span>;<\/span> R -=<\/span> lr *<\/span> gR
\n return<\/span> E,<\/span> R<\/p>\n

def<\/span> train_transr<\/span>(<\/span>steps=<\/span>1500<\/span>,<\/span> lr=<\/span>0.05<\/span>,<\/span> bs=<\/span>64<\/span>)<\/span>:<\/span>
\n E =<\/span> unit(<\/span>rng.<\/span>randn(<\/span>N_ENT,<\/span> DIM)<\/span>)<\/span>;<\/span> R =<\/span> rng.<\/span>randn(<\/span>3<\/span>,<\/span> DIM)<\/span> *<\/span> 0.1<\/span>
\n M =<\/span> np.<\/span>array(<\/span>[<\/span>np.<\/span>eye(<\/span>DIM)<\/span> +<\/span> 0.01<\/span> *<\/span> rng.<\/span>randn(<\/span>DIM,<\/span> DIM)<\/span> for<\/span> _ in<\/span> range<\/span>(<\/span>3<\/span>)<\/span>]<\/span>)<\/span> # \u5355\u4f4d\u9635+\u5c0f\u6270\u52a8<\/span>
\n for<\/span> _ in<\/span> range<\/span>(<\/span>steps)<\/span>:<\/span>
\n h,<\/span> r,<\/span> t =<\/span> T[<\/span>rng.<\/span>randint(<\/span>0<\/span>,<\/span> len<\/span>(<\/span>T)<\/span>,<\/span> bs)<\/span>]<\/span>.<\/span>T
\n nt =<\/span> rng.<\/span>randint(<\/span>0<\/span>,<\/span> N_ENT,<\/span> bs)<\/span>
\n Mr =<\/span> M[<\/span>r]<\/span>
\n ph =<\/span> np.<\/span>einsum(<\/span>"nij,nj->ni"<\/span>,<\/span> Mr,<\/span> E[<\/span>h]<\/span>)<\/span> # \u6295\u5f71\u5230\u5173\u7cfb\u7a7a\u95f4<\/span>
\n vp =<\/span> ph +<\/span> R[<\/span>r]<\/span> –<\/span> np.<\/span>einsum(<\/span>"nij,nj->ni"<\/span>,<\/span> Mr,<\/span> E[<\/span>t]<\/span>)<\/span>
\n vn =<\/span> ph +<\/span> R[<\/span>r]<\/span> –<\/span> np.<\/span>einsum(<\/span>"nij,nj->ni"<\/span>,<\/span> Mr,<\/span> E[<\/span>nt]<\/span>)<\/span>
\n np_ =<\/span> np.<\/span>linalg.<\/span>norm(<\/span>vp,<\/span> axis=<\/span>1<\/span>)<\/span> +<\/span> 1e-9<\/span>
\n nn_ =<\/span> np.<\/span>linalg.<\/span>norm(<\/span>vn,<\/span> axis=<\/span>1<\/span>)<\/span> +<\/span> 1e-9<\/span>
\n m =<\/span> (<\/span>(<\/span>GAMMA +<\/span> np_ –<\/span> nn_)<\/span> ><\/span> 0<\/span>)<\/span>.<\/span>astype(<\/span>float<\/span>)<\/span>
\n gp =<\/span> (<\/span>m \/<\/span> np_)<\/span>[<\/span>:<\/span>,<\/span> None<\/span>]<\/span> *<\/span> vp
\n gn =<\/span> –<\/span>(<\/span>m \/<\/span> nn_)<\/span>[<\/span>:<\/span>,<\/span> None<\/span>]<\/span> *<\/span> vn
\n gE =<\/span> np.<\/span>zeros_like(<\/span>E)<\/span>;<\/span> gR =<\/span> np.<\/span>zeros_like(<\/span>R)<\/span>;<\/span> gM =<\/span> np.<\/span>zeros_like(<\/span>M)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gE,<\/span> h,<\/span> np.<\/span>einsum(<\/span>"nij,ni->nj"<\/span>,<\/span> Mr,<\/span> gp)<\/span>)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gE,<\/span> t,<\/span> np.<\/span>einsum(<\/span>"nij,ni->nj"<\/span>,<\/span> Mr,<\/span> –<\/span>gp)<\/span>)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gR,<\/span> r,<\/span> gp)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gM,<\/span> r,<\/span> gp[<\/span>:<\/span>,<\/span> :<\/span>,<\/span> None<\/span>]<\/span> *<\/span> E[<\/span>h]<\/span>[<\/span>:<\/span>,<\/span> None<\/span>,<\/span> :<\/span>]<\/span> –<\/span> gp[<\/span>:<\/span>,<\/span> :<\/span>,<\/span> None<\/span>]<\/span> *<\/span> E[<\/span>t]<\/span>[<\/span>:<\/span>,<\/span> None<\/span>,<\/span> :<\/span>]<\/span>)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gE,<\/span> h,<\/span> np.<\/span>einsum(<\/span>"nij,ni->nj"<\/span>,<\/span> Mr,<\/span> gn)<\/span>)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gE,<\/span> nt,<\/span> np.<\/span>einsum(<\/span>"nij,ni->nj"<\/span>,<\/span> Mr,<\/span> –<\/span>gn)<\/span>)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gR,<\/span> r,<\/span> gn)<\/span>
\n np.<\/span>add.<\/span>at(<\/span>gM,<\/span> r,<\/span> gn[<\/span>:<\/span>,<\/span> :<\/span>,<\/span> None<\/span>]<\/span> *<\/span> E[<\/span>h]<\/span>[<\/span>:<\/span>,<\/span> None<\/span>,<\/span> :<\/span>]<\/span> –<\/span> gn[<\/span>:<\/span>,<\/span> :<\/span>,<\/span> None<\/span>]<\/span> *<\/span> E[<\/span>nt]<\/span>[<\/span>:<\/span>,<\/span> None<\/span>,<\/span> :<\/span>]<\/span>)<\/span>
\n E =<\/span> unit(<\/span>E –<\/span> lr *<\/span> gE)<\/span>;<\/span> R -=<\/span> lr *<\/span> gR;<\/span> M -=<\/span> lr *<\/span> gM
\n return<\/span> E,<\/span> R,<\/span> M<\/p>\n

def<\/span> region_ratio<\/span>(<\/span>E)<\/span>:<\/span>
\n C =<\/span> E[<\/span>C0:<\/span>C0 +<\/span> N_CITY]<\/span>
\n D =<\/span> np.<\/span>linalg.<\/span>norm(<\/span>C[<\/span>:<\/span>,<\/span> None<\/span>,<\/span> :<\/span>]<\/span> –<\/span> C[<\/span>None<\/span>,<\/span> :<\/span>,<\/span> :<\/span>]<\/span>,<\/span> axis=<\/span>2<\/span>)<\/span>
\n same =<\/span> city_region[<\/span>:<\/span>,<\/span> None<\/span>]<\/span> ==<\/span> city_region[<\/span>None<\/span>,<\/span> :<\/span>]<\/span>
\n iu =<\/span> np.<\/span>triu_indices(<\/span>N_CITY,<\/span> k=<\/span>1<\/span>)<\/span>
\n intra =<\/span> D[<\/span>iu]<\/span>[<\/span>same[<\/span>iu]<\/span>]<\/span>.<\/span>mean(<\/span>)<\/span>;<\/span> inter =<\/span> D[<\/span>iu]<\/span>[<\/span>~<\/span>same[<\/span>iu]<\/span>]<\/span>.<\/span>mean(<\/span>)<\/span>
\n return<\/span> intra,<\/span> inter,<\/span> intra \/<\/span> inter<\/p>\n

E1,<\/span> _ =<\/span> train_transe(<\/span>)<\/span>
\na1,<\/span> b1,<\/span> q1 =<\/span> region_ratio(<\/span>E1)<\/span>
\nprint<\/span>(<\/span>"TransE \u540c\u5730\u533a\/\u8de8\u5730\u533a\u5e73\u5747\u8ddd\u79bb = %.3f \/ %.3f，\u6bd4\u503c %.2f"<\/span> %<\/span> (<\/span>a1,<\/span> b1,<\/span> q1)<\/span>)<\/span><\/p>\n

E2,<\/span> _,<\/span> _ =<\/span> train_transr(<\/span>)<\/span>
\na2,<\/span> b2,<\/span> q2 =<\/span> region_ratio(<\/span>E2)<\/span>
\nprint<\/span>(<\/span>"TransR \u540c\u5730\u533a\/\u8de8\u5730\u533a\u5e73\u5747\u8ddd\u79bb = %.3f \/ %.3f，\u6bd4\u503c %.2f"<\/span> %<\/span> (<\/span>a2,<\/span> b2,<\/span> q2)<\/span>)<\/span><\/p>\n

\u8fd0\u884c\u7ed3\u679c\u8bf4\u660e：TransE \u8bad\u7ec3\u540e，\u540c\u5730\u533a\u57ce\u5e02\u4e4b\u95f4\u7684\u5e73\u5747\u8ddd\u79bb\u53ea\u6709\u8de8\u5730\u533a\u8ddd\u79bb\u7684\u7ea6 0.27 \u500d\u2014\u2014\u8fd9\u5c31\u662f"\u591a\u5bf9\u4e00\u538b\u7f29"\u7684\u91cf\u5316\u8bc1\u636e：\u672c\u8be5\u88ab\u62c9\u5f00\u7684\u4e24\u5ea7\u540c\u5730\u533a\u57ce\u5e02，\u88ab\u6a21\u578b\u6324\u5230\u4e86\u4e00\u8d77\u3002\u800c TransR \u5f15\u5165\u6295\u5f71\u77e9\u9635 Mr\\\\mathbf M_r<\/span><\/span>M<\/span><\/span>r<\/span><\/span><\/span><\/span>\u200b<\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span><\/span> \u540e，\u5148\u5728\u5173\u7cfb\u7a7a\u95f4\u91cc\u505a\u4e00\u6b21\u5750\u6807\u53d8\u6362\u518d\u7b97\u8ddd\u79bb，\u8fd9\u4e2a\u6bd4\u503c\u88ab\u6491\u5f00\u5230\u4e86\u7ea6 0.84，\u540c\u5730\u533a\u57ce\u5e02\u7684\u76f8\u5bf9\u7ed3\u6784\u660e\u663e\u66f4\u8212\u5c55，\u9488\u5bf9"\u4f4d\u4e8e"\u8fd9\u4e2a\u591a\u5bf9\u4e00\u5173\u7cfb\u505a\u5934\u9884\u6d4b\u65f6，\u5e73\u5747\u6392\u540d\u4e0e MRR \u90fd\u80fd\u6539\u5584\u3002\u5f53\u7136，\u6295\u5f71\u77e9\u9635\u53c2\u6570\u66f4\u591a，\u5728\u5c0f\u56fe\u8c31\u4e0a\u5bb9\u6613\u6b20\u62df\u5408，\u6574\u4f53 Hits@k \u672a\u5fc5\u66f4\u597d，\u8981\u7ed3\u5408\u6570\u636e\u91cf\u4e00\u8d77\u770b\u3002<\/p>\n

\u56db\u3001\u5173\u952e\u7ecf\u9a8c\/\u907f\u5751<\/h3>\n
  • \u5b9e\u4f53\u5411\u91cf\u5fc5\u987b\u5f52\u4e00\u5316：\u4e0d\u5f52\u4e00\u5316，\u6a21\u578b\u4f1a\u9760\u6574\u4f53\u653e\u5927\u8ddd\u79bb\u6765\u538b\u4f4e\u635f\u5931，\u5b66\u51fa\u6765\u7684\u51e0\u4f55\u5168\u662f\u5c3a\u5ea6\u566a\u58f0\u3002<\/li>\n
  • \u8d1f\u91c7\u6837\u8981\u6309\u7c7b\u578b\u9650\u5b9a\u5019\u9009\u6c60：\u8ba9"\u4eba\u7269"\u53bb\u5f53"\u4f4d\u4e8e"\u7684\u5c3e\u5b9e\u4f53，\u662f\u7eaf\u7cb9\u7684\u6d6a\u8d39\u7b97\u529b\u3002<\/li>\n
  • \u522b\u53ea\u8bc4\u5c3e\u9884\u6d4b：\u591a\u5bf9\u4e00\u3001\u4e00\u5bf9\u591a\u5173\u7cfb\u7684\u7f3a\u9677\u4f1a\u88ab\u5c3e\u9884\u6d4b\u63a9\u76d6，\u52a1\u5fc5\u8865\u4e0a\u5934\u9884\u6d4b（\u6216\u5934\u5c3e\u90fd\u8bc4）\u3002<\/li>\n
  • \u53c2\u6570\u591a\u4e0d\u7b49\u4e8e\u6548\u679c\u597d：TransR \u7684\u6295\u5f71\u77e9\u9635\u5728\u5c0f\u56fe\u8c31\u4e0a\u660e\u663e\u6b20\u62df\u5408，\u53c2\u6570\u91cf\u8981\u8ddf\u6570\u636e\u91cf\u4e00\u8d77\u770b\u3002<\/li>\n
  • \u6295\u5f71\u77e9\u9635\u521d\u59cb\u5316\u5f88\u5173\u952e：\u4ece\u5355\u4f4d\u9635 + \u5c0f\u6270\u52a8\u51fa\u53d1，\u6a21\u578b\u80fd\u5e73\u6ed1\u5730\u4ece"\u5e73\u79fb"\u8fc7\u6e21\u5230"\u6295\u5f71"，\u6bd4\u7eaf\u968f\u673a\u6536\u655b\u7a33\u5f97\u591a\u3002<\/li>\n
  • \u4fdd\u7559\u53ef\u8bfb\u7684\u4e2d\u95f4\u91cf：\u50cf"\u540c\u5730\u533a\/\u8de8\u5730\u533a\u8ddd\u79bb\u6bd4"\u8fd9\u6837\u7684\u8bca\u65ad\u6307\u6807，\u6bd4\u5355\u770b Hits@k \u66f4\u80fd\u89e3\u91ca\u6a21\u578b\u5230\u5e95\u5b66\u5230\u4e86\u4ec0\u4e48\u3002<\/li>\n

    \u4e94\u3001\u5b8c\u6574\u7cfb\u5217\u63a8\u8350<\/h3>\n

    📚 \u672c\u6587\u9009\u81ea\u300a\u56fe\u795e\u7ecf\u7f51\u7edc\u4e0e\u56fe\u6df1\u5ea6\u5b66\u4e60\u300b100 \u671f\u7cfb\u7edf\u6559\u7a0b（\u7b2c 069 \u671f：TransE \u4e0e TransR \u5bb6\u65cf），\u6bcf\u671f\u914d\u53ef\u8fd0\u884c Python \u4ee3\u7801\u3002<\/p>\n

    \u5b8c\u6574\u7cfb\u5217（100 \u671f\u6b63\u6587 + 3 \u7bc7\u756a\u5916，\u6bcf\u671f\u6587\u7ae0+\u4ee3\u7801）\u5df2\u5728 ima \u77e5\u8bc6\u53f7\u3010Kruptos\u3011\u6301\u7eed\u66f4\u65b0：<\/p>\n

      \n
    • 🗂 70+ \u6280\u672f\u77e5\u8bc6\u5e93：\u56fe\u795e\u7ecf\u7f51\u7edc\u3001\u5f3a\u5316\u5b66\u4e60\u3001\u8ba1\u7b97\u673a\u89c6\u89c9\u3001\u63a8\u8350\u7cfb\u7edf\u3001\u5927\u6a21\u578b\u5fae\u8c03\u3001\u64cd\u4f5c\u7cfb\u7edf\u2026\u2026\u51e0\u4e4e\u8986\u76d6\u5168\u90e8\u8f6f\u786c\u4ef6\u6280\u672f\u6808<\/li>\n
    • 🧠 8 \u6b3e AI \u6280\u80fd：\u7cfb\u5217\u751f\u4ea7\u3001\u77e5\u8bc6\u5e93\u7ba1\u7406\u3001CMMI \u53d7\u7ba1\u5f00\u53d1\u3001\u81ea\u8fdb\u5316 Agent \u7b49，\u5df2\u5728 ima \u6280\u80fd\u5e7f\u573a\u4e0a\u67b6，\u5373\u88c5\u5373\u7528<\/li>\n
    • \u2705 \u5168\u90e8\u514d\u8d39\u8ba2\u9605，\u540e\u7eed\u66f4\u65b0\u81ea\u52a8\u63a8\u9001<\/li>\n<\/ul>\n

      🔍 \u8ba2\u9605\u65b9\u5f0f：\u6253\u5f00 ima（\u817e\u8baf\u667a\u80fd\u5de5\u4f5c\u53f0）\u2192 \u641c\u7d22\u300cKruptos\u300d\u2192 \u4e00\u952e\u8ba2\u9605；\u6216\u5728 ima \u5185\u76f4\u63a5\u641c\u7d22\u300a\u56fe\u795e\u7ecf\u7f51\u7edc\u4e0e\u56fe\u6df1\u5ea6\u5b66\u4e60\u300b\u3002<\/p>\n

      \n

      \u4f5c\u8005：Kruptos（\u897f\u7535\u6bd5\u4e1a，13 \u5e74\u65e0\u7ebf\u901a\u4fe1\/DSP\/\u5d4c\u5165\u5f0f\u79d1\u7814，\u73b0\u6df1\u8015 AI \u4e0e\u4e91\u539f\u751f）
      \n\u539f\u521b\u5185\u5bb9，\u8f6c\u8f7d\u6ce8\u660e\u51fa\u5904\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

      TransE \u4e00\u4e2a\u5411\u91cf\u7b49\u5f0f，\u8ba9\u77e5\u8bc6\u56fe\u8c31\u5b66\u4f1a\u63a8\u7406\u4e00\u53e5\u8bdd\u5bfc\u8bed：\u628a\u5173\u7cfb\u5f53\u6210\u4e00\u6b21\u5e73\u79fb，\u201c\u5934\u5b9e\u4f53 \u5173\u7cfb \u2248 \u5c3e\u5b9e\u4f53\u201d，\u77e5\u8bc6\u56fe\u8c31\u5c31\u80fd\u5728\u5411\u91cf\u7a7a\u95f4\u91cc\u505a\u63a8\u7406\u2014\u2014\u4f46\u5b83\u683d\u5728\u4e86\u591a\u5bf9\u4e00\u5173\u7cfb\u4e0a\u3002\u4e00\u3001\u80cc\u666f\u4e0e\u75db\u70b9
      \n\u77e5\u8bc6\u56fe\u8c31\u91cc\u5b58\u7684\u662f\\”\u5f20\u4e09\u2014\u5c31\u804c\u4e8e\u2014\u67d0\u516c\u53f8\\”\\”\u5317\u4eac\u2014\u4f4d\u4e8e\u2014\u534e\u5317\\”\u8fd9\u6837\u7684\u4e09\u5143\u7ec4\u4e8b\u5b9e\u3002\u53ef\u771f\u5b9e\u56fe\u8c31\u6c38\u8fdc\u662f\u4e0d\u5b8c\u6574\u7684：\u5927\u91cf\u5173\u7cfb\u7f3a\u5931，\u9700\u8981\u6211\u4eec\u6839\u636e\u5df2\u6709\u4e8b\u5b9e\u53bb\u63a8\u65ad\u90a3\u6761\u7f3a\u5931\u7684\u8fb9，\u4e5f\u5c31\u662f\u94fe\u63a5\u9884\u6d4b\u3002\u65e9\u671f\u505a\u6cd5\u662f\u7eaf\u7b26\u53f7\u903b\u8f91&#<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[11934,11653,11935,613],"topic":[],"class_list":["post-105151","post","type-post","status-publish","format-standard","hentry","category-server","tag-transe","tag-11653","tag-11935","tag-613"],"yoast_head":"\nTransE \u4e00\u4e2a\u5411\u91cf\u7b49\u5f0f\uff0c\u8ba9\u77e5\u8bc6\u56fe\u8c31\u5b66\u4f1a\u63a8\u7406 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/105151.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"TransE \u4e00\u4e2a\u5411\u91cf\u7b49\u5f0f\uff0c\u8ba9\u77e5\u8bc6\u56fe\u8c31\u5b66\u4f1a\u63a8\u7406 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"og:description\" content=\"TransE \u4e00\u4e2a\u5411\u91cf\u7b49\u5f0f，\u8ba9\u77e5\u8bc6\u56fe\u8c31\u5b66\u4f1a\u63a8\u7406\u4e00\u53e5\u8bdd\u5bfc\u8bed：\u628a\u5173\u7cfb\u5f53\u6210\u4e00\u6b21\u5e73\u79fb，\u201c\u5934\u5b9e\u4f53 \u5173\u7cfb \u2248 \u5c3e\u5b9e\u4f53\u201d，\u77e5\u8bc6\u56fe\u8c31\u5c31\u80fd\u5728\u5411\u91cf\u7a7a\u95f4\u91cc\u505a\u63a8\u7406\u2014\u2014\u4f46\u5b83\u683d\u5728\u4e86\u591a\u5bf9\u4e00\u5173\u7cfb\u4e0a\u3002\u4e00\u3001\u80cc\u666f\u4e0e\u75db\u70b9 \u77e5\u8bc6\u56fe\u8c31\u91cc\u5b58\u7684\u662f"\u5f20\u4e09\u2014\u5c31\u804c\u4e8e\u2014\u67d0\u516c\u53f8""\u5317\u4eac\u2014\u4f4d\u4e8e\u2014\u534e\u5317"\u8fd9\u6837\u7684\u4e09\u5143\u7ec4\u4e8b\u5b9e\u3002\u53ef\u771f\u5b9e\u56fe\u8c31\u6c38\u8fdc\u662f\u4e0d\u5b8c\u6574\u7684：\u5927\u91cf\u5173\u7cfb\u7f3a\u5931，\u9700\u8981\u6211\u4eec\u6839\u636e\u5df2\u6709\u4e8b\u5b9e\u53bb\u63a8\u65ad\u90a3\u6761\u7f3a\u5931\u7684\u8fb9，\u4e5f\u5c31\u662f\u94fe\u63a5\u9884\u6d4b\u3002\u65e9\u671f\u505a\u6cd5\u662f\u7eaf\u7b26\u53f7\u903b\u8f91&#\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.wsisp.com\/helps\/105151.html\" \/>\n<meta property=\"og:site_name\" content=\"\u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3\" \/>\n<meta property=\"article:published_time\" content=\"2026-09-14T16:16:20+00:00\" \/>\n<meta name=\"author\" content=\"admin\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"\u4f5c\u8005\" \/>\n\t<meta name=\"twitter:data1\" content=\"admin\" \/>\n\t<meta name=\"twitter:label2\" content=\"\u9884\u8ba1\u9605\u8bfb\u65f6\u95f4\" \/>\n\t<meta name=\"twitter:data2\" content=\"6 \u5206\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.wsisp.com\/helps\/105151.html\",\"url\":\"https:\/\/www.wsisp.com\/helps\/105151.html\",\"name\":\"TransE \u4e00\u4e2a\u5411\u91cf\u7b49\u5f0f\uff0c\u8ba9\u77e5\u8bc6\u56fe\u8c31\u5b66\u4f1a\u63a8\u7406 - 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