{"id":3739,"date":"2025-07-17T22:08:47","date_gmt":"2025-07-17T14:08:47","guid":{"rendered":"https:\/\/www.15zhi.net\/blog\/?p=3739"},"modified":"2025-07-17T22:08:47","modified_gmt":"2025-07-17T14:08:47","slug":"202507-%e8%ae%ba%e6%96%87%e7%a0%94%e8%af%bb-large-language-models-for-intent-driven-session-recommendations","status":"publish","type":"post","link":"https:\/\/www.15zhi.net\/blog\/202507-%e8%ae%ba%e6%96%87%e7%a0%94%e8%af%bb-large-language-models-for-intent-driven-session-recommendations\/","title":{"rendered":"202507 \u8bba\u6587\u7814\u8bfb-Large Language Models for Intent-Driven Session Recommendations"},"content":{"rendered":"\n

\u6765\u6e90\uff1aACM SIGIR
\u4f5c\u8005\uff1aZhu Sun, Hongyang Liu\u7b49
\u5355\u4f4d\uff1aA*STAR Centre for Frontier AI Research, Singapore\u3001\u65b0\u52a0\u5761\u79d1\u6280\u8bbe\u8ba1\u5927\u5b66\u7b49.
\u53d1\u8868\u65f6\u95f4\uff1a2024 \u5e74 6 \u6708<\/p>\n\n\n\n

\u7814\u7a76\u80cc\u666f<\/h2>\n\n\n\n
    \n
  1. \u610f\u56fe\u611f\u77e5\u63a8\u8350\u7cfb\u7edf\uff08ISR\uff09\u7684\u9700\u6c42<\/li>\n<\/ol>\n\n\n\n

    \u4f1a\u8bdd\u63a8\u8350\u7cfb\u7edf\u7684\u76ee\u6807\u662f\u6839\u636e\u7528\u6237\u5728\u4e00\u4e2a\u77ed\u6682\u7684\u533f\u540d\u4f1a\u8bdd\u4e2d\u7684\u884c\u4e3a\u6765\u9884\u6d4b\u7528\u6237\u53ef\u80fd\u611f\u5174\u8da3\u7684\u4e0b\u4e00\u4e2a\u9879\u76ee\u3002
    \u5b9e\u9645\u573a\u666f\u4e2d\uff0c\u7528\u6237\u5728\u540c\u4e00\u4f1a\u8bdd\u5185\u53ef\u80fd\u6709\u591a\u4e2a\u5e76\u884c\u7684\u610f\u56fe\u3002
    ISR\u5373\u901a\u8fc7\u8bc6\u522b\u548c\u5efa\u6a21\u7528\u6237\u5728\u5355\u6b21\u4f1a\u8bdd\u4e2d\u53ef\u80fd\u7684\u591a\u91cd\u610f\u56fe\u6765\u63d0\u9ad8\u63a8\u8350\u7684\u51c6\u786e\u6027\u548c\u591a\u6837\u6027\u3002<\/p>\n\n\n\n

      \n
    1. LLM\u7684\u5e94\u7528
      \u5728\u4f1a\u8bdd\u63a8\u8350\u7cfb\u7edf\u4e2d\uff0cLLM\u53ef\u4ee5\u63d0\u4f9b\u4ee5\u4e0b\u4f18\u52bf\uff1a<\/li>\n<\/ol>\n\n\n\n

      \u63a8\u7406\u80fd\u529b\uff1aLLM\u5177\u5907\u5f3a\u5927\u7684\u63a8\u7406\u80fd\u529b\uff0c\u53ef\u4ee5\u5e2e\u52a9\u7406\u89e3\u548c\u5efa\u6a21\u7528\u6237\u5728\u6bcf\u4e2a\u4f1a\u8bdd\u4e2d\u7684\u591a\u91cd\u610f\u56fe\u3002\u4f8b\u5982\uff0c\u5b83\u4eec\u80fd\u591f\u4ece\u7528\u6237\u7684\u591a\u4e2a\u884c\u4e3a\u4e2d\u63a8\u6d4b\u51fa\u80cc\u540e\u7684\u4e0d\u540c\u76ee\u6807\u3002<\/p>\n\n\n\n

      \u8bed\u4e49\u7406\u89e3\uff1aLLM\u4e0d\u4ec5\u4ec5\u4f9d\u8d56\u4e8e\u5355\u4e00\u7684\u610f\u56fe\u6807\u7b7e\uff0c\u800c\u662f\u80fd\u591f\u5728\u8bed\u4e49\u5c42\u9762\u4e0a\u63a8\u65ad\u7528\u6237\u7684\u771f\u5b9e\u9700\u6c42\u3002\u8fd9\u4f7f\u5f97\u5b83\u4eec\u80fd\u66f4\u597d\u5730\u7406\u89e3\u7528\u6237\u590d\u6742\u7684\u8d2d\u4e70\u51b3\u7b56\u8fc7\u7a0b\u3002<\/p>\n\n\n\n

      \u8fd9\u7bc7\u6587\u7ae0\u63d0\u51fa\uff1aLLM4ISR\uff08Large Language Models for Intent-Driven Session Recommendations\uff09
      \u7ed3\u5408\u4e86LLMs\u7684\u63a8\u7406\u80fd\u529b\u548c\u4f18\u5316\u673a\u5236\uff0c\u4ece\u800c\u80fd\u591f\u66f4\u597d\u5730\u6355\u6349\u548c\u7406\u89e3\u7528\u6237\u7684\u591a\u91cd\u610f\u56fe\u3002<\/p>\n\n\n\n

      LLM4ISR\u65b9\u6cd5<\/h2>\n\n\n\n
      \"\"<\/figure>\n\n\n\n

      LLM4ISR\uff1a\u901a\u8fc7\u7cbe\u7ec6\u7684\u63d0\u793a\u8bbe\u8ba1\u548c\u4f18\u5316\u673a\u5236\uff0c\u6709\u6548\u5730\u89e3\u51b3\u591a\u91cd\u610f\u56fe\u8bc6\u522b\u548c\u63a8\u8350\u900f\u660e\u5ea6\u4e0d\u8db3\u7684\u95ee\u9898\u3002<\/p>\n\n\n\n

        \n
      • Prompt Initialization<\/li>\n<\/ul>\n\n\n\n
        \"\"<\/figure>\n\n\n\n
        \"\"<\/figure>\n\n\n\n

        \u63d0\u793a\u521d\u59cb\u5316\u662fLLM4ISR\u7684\u7b2c\u4e00\u4e2a\u6a21\u5757\uff0c\u65e8\u5728\u4e3aLLM\u751f\u6210\u4e00\u4e2a\u521d\u59cb\u7684\u4efb\u52a1\u63cf\u8ff0\u63d0\u793a\uff0c\u5e2e\u52a9\u6a21\u578b\u7406\u89e3\u7528\u6237\u4f1a\u8bdd\u4e2d\u7684\u610f\u56fe\u3002<\/p>\n\n\n\n


        \u901a\u8fc7\u8bbe\u8ba1\u7cbe\u786e\u7684\u4efb\u52a1\u63cf\u8ff0\uff0c\u6a21\u578b\u80fd\u591f\u5728\u521d\u6b65\u9636\u6bb5\u63a8\u6d4b\u51fa\u7528\u6237\u7684\u884c\u4e3a\u6a21\u5f0f\u548c\u610f\u56fe\u3002
        \u8bc6\u522b\u4f1a\u8bdd\u4e2d\u7684\u4e0d\u540c\u9879\u7ec4\u5408<\/p>\n\n\n\n


        \u63a8\u6d4b\u6bcf\u4e2a\u7ec4\u5408\u7684\u7528\u6237\u610f\u56fe
        \u9009\u62e9\u6700\u7b26\u5408\u7528\u6237\u5f53\u524d\u504f\u597d\u7684\u610f\u56fe
        \u6839\u636e\u9009\u5b9a\u7684\u610f\u56fe\u91cd\u65b0\u6392\u5e8f\u5019\u9009\u9879\u76ee<\/p>\n\n\n\n


        \u901a\u8fc7\u8fd9\u79cd\u65b9\u5f0f\uff0cLLM4ISR\u4e3a\u540e\u7eed\u7684\u63a8\u8350\u8fc7\u7a0b\u5960\u5b9a\u4e86\u57fa\u7840\uff0c\u4f7fLLM\u80fd\u591f\u7406\u89e3\u5e76\u63a8\u7406\u7528\u6237\u4f1a\u8bdd\u4e2d\u7684\u610f\u56fe\u3002<\/p>\n\n\n\n

          \n
        • Prompt Optimization<\/li>\n<\/ul>\n\n\n\n
          \"\"<\/figure>\n\n\n\n

          \u5173\u952e\u6b65\u9aa4\u5305\u62ec\uff1a\u9519\u8bef\u6848\u4f8b\u6536\u96c6\u3001\u63a8\u7406\u9519\u8bef\u539f\u56e0\u3001\u6539\u8fdb\u63d0\u793a\u3001\u5e76\u901a\u8fc7UCB\uff08Upper Confidence Bound\uff09Bandits\u7b56\u7565\u8fdb\u884c\u6027\u80fd\u8bc4\u4f30\u3002<\/p>\n\n\n\n

          \u5177\u4f53\u6d41\u7a0b\u5982\u4e0b\uff1a
          \u9519\u8bef\u6848\u4f8b\u6536\u96c6\uff08Collecting Error Cases\uff09
          \u63a8\u7406\u9519\u8bef\u539f\u56e0\uff08Inferring Reasons for Errors\uff09
          \u4f18\u5316\u63d0\u793a\uff08Refining Prompts\uff09
          \u589e\u5f3a\u63d0\u793a\uff08Augmenting Prompts\uff09<\/p>\n\n\n\n


          UCB Bandits\u7b56\u7565
          \u63d0\u793a\u4f18\u5316\u6a21\u5757\u901a\u8fc7\u4e0d\u65ad\u5730\u6536\u96c6\u9519\u8bef\u6848\u4f8b\u3001\u5206\u6790\u9519\u8bef\u539f\u56e0\u3001\u4f18\u5316\u548c\u589e\u5f3a\u63d0\u793a\uff0c\u4ee5\u53ca\u5229\u7528UCB Bandits\u7b56\u7565\u8fdb\u884c\u6027\u80fd\u8bc4\u4f30\uff0c\u6700\u7ec8\u5b9e\u73b0\u4e86\u5bf9LLM\u63d0\u793a\u7684\u4e0d\u65ad\u6539\u8fdb\u548c\u4f18\u5316\u3002<\/p>\n\n\n\n

          \"\"<\/figure>\n\n\n\n
            \n
          • Prompt Selection<\/li>\n<\/ul>\n\n\n\n
            \"\"<\/figure>\n\n\n\n
            \"\"<\/figure>\n\n\n\n

            \u63d0\u793a\u9009\u62e9\u662fLLM4ISR\u7684\u7b2c\u4e09\u4e2a\u6a21\u5757\uff0c\u5b83\u901a\u8fc7\u8bc4\u4f30\u548c\u9009\u62e9\u6700\u4f18\u7684\u63d0\u793a\u6765\u8fdb\u4e00\u6b65\u63d0\u5347\u63a8\u8350\u6548\u679c\u3002
            \u5176\u4e3b\u8981\u76ee\u7684\u662f\u4ece\u591a\u4e2a\u4f18\u5316\u540e\u7684\u63d0\u793a\u4e2d\u9009\u62e9\u6700\u4f18\u7684\u63d0\u793a\uff0c\u4ee5\u786e\u4fdd\u63a8\u8350\u7cfb\u7edf\u5728\u4e0d\u540c\u6570\u636e\u96c6\u4e0a\u7684\u8868\u73b0\u8fbe\u5230\u6700\u4f73\u3002
            \u6700\u4f18\u63d0\u793a\u9009\u62e9\uff1aGames\u6570\u636e\u96c6\u7684Top-1\u63d0\u793a\u5728\u6240\u6709\u6570\u636e\u96c6\u4e0a\u7684\u8868\u73b0\u6700\u4f18\u3002\u56e0\u6b64\uff0cGames\u6570\u636e\u96c6\u7684Top-1\u63d0\u793a\u88ab\u9009\u4e3a\u6700\u7ec8\u7684\u6700\u4f18\u63d0\u793a\uff0c\u7528\u4e8e\u8de8\u9886\u57df\u63a8\u8350\u4efb\u52a1\u3002<\/p>\n\n\n\n

            \u5b9e\u9a8c<\/h2>\n\n\n\n
            \"\"<\/figure>\n\n\n\n

            \u57fa\u7ebf\u65b9\u6cd5 (Baselines)—11\u79cd\u57fa\u7ebf\u65b9\u6cd5\uff1a<\/p>\n\n\n\n


            \u4f20\u7edf\u65b9\u6cd5 (Conventional Methods)\uff1a
            MostPop\uff1a\u63a8\u8350\u6700\u53d7\u6b22\u8fce\u7684\u5546\u54c1\u3002
            SKNN\uff1a\u57fa\u4e8e\u4f1a\u8bdd\u7ea7\u522b\u7684\u7269\u54c1\u76f8\u4f3c\u5ea6\u8fdb\u884c\u63a8\u8350\u3002
            FPMC\uff1a\u4f7f\u7528\u57fa\u4e8e\u9a6c\u5c14\u53ef\u592b\u94fe\u7684\u77e9\u9635\u5206\u89e3\u65b9\u6cd5\u3002
            \u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5 (Deep Learning Methods)\uff1a
            \u5305\u62ec\u57fa\u4e8e\u5355\u4e00\u610f\u56fe\u548c\u591a\u610f\u56fe\u7684\u63a8\u8350\u65b9\u6cd5\uff0c\u5982NARM\uff08\u57fa\u4e8eRNN\u7684\u6a21\u578b\uff09\u3001STAMP\uff08\u901a\u8fc7\u6ce8\u610f\u529b\u673a\u5236\u5b66\u4e60\u7528\u6237\u7684\u4e3b\u8981\u610f\u56fe\uff09\u3001MCPRN\uff08\u591a\u901a\u9053\u76ee\u7684\u8def\u7531\u7f51\u7edc\uff09\u3001HIDE\uff08\u901a\u8fc7\u5206\u5272\u5d4c\u5165\u8868\u793a\u591a\u4e2a\u610f\u56fe\uff09\u7b49\u3002
            \u8de8\u9886\u57df\u65b9\u6cd5 (Cross-domain Methods)\uff1a
            UniSRec\uff1a\u8de8\u57df\u5b66\u4e60\u6a21\u578b\uff0c\u4f7f\u7528\u9879\u63cf\u8ff0\u6765\u5b66\u4e60\u53ef\u8f6c\u79fb\u7684\u8868\u793a\u3002
            \u57fa\u4e8eLLM\u7684\u65b9\u6cd5 (LLM-based Methods)\uff1a
            NIR\uff1a\u901a\u8fc7\u96f6-shot\u63d0\u793a\u8fdb\u884c\u63a8\u8350\u3002<\/p>\n\n\n\n

              \n
            • \u6574\u4f53\u5bf9\u6bd4<\/li>\n<\/ul>\n\n\n\n
              \"\"<\/figure>\n\n\n\n

              \u7ed3\u8bba\uff1a
              \u8bba\u6587\u9996\u5148\u5bf9LLM4ISR\u4e0e\u5404\u57fa\u7ebf\u65b9\u6cd5\u5728\u4e09\u4e2a\u6570\u636e\u96c6\u4e0a\u7684\u8868\u73b0\u8fdb\u884c\u4e86\u5bf9\u6bd4\u3002\u7ed3\u679c\u8868\u660e\uff0cLLM4ISR\u5728\u6240\u6709\u4e09\u4e2a\u6570\u636e\u96c6\u4e0a\u90fd\u4f18\u4e8e\u5176\u4ed6\u57fa\u7ebf\u65b9\u6cd5\uff0c\u5c24\u5176\u662f\u5728\u7a00\u758f\u6570\u636e\u548c\u77ed\u4f1a\u8bdd\u7684\u573a\u666f\u4e2d\u8868\u73b0\u51fa\u8272\u3002<\/p>\n\n\n\n

                \n
              • \u6d88\u878d\u5b9e\u9a8c<\/li>\n<\/ul>\n\n\n\n
                \"\"<\/figure>\n\n\n\n

                Initial\uff1a\u4ec5\u4f7f\u7528\u521d\u59cb\u63d0\u793a\u3002
                Top-1\uff1a\u4ec5\u4f7f\u7528Top-1\u63d0\u793a\u3002
                EnSame\uff1a\u5c06Top-1\u548cTop-2\u63d0\u793a\u7684\u7ed3\u679c\u8fdb\u884c\u96c6\u6210\u3002
                EnCross\uff1a\u5c06\u6765\u81ea\u6240\u6709\u6570\u636e\u96c6\u7684Top-1\u63d0\u793a\u7ed3\u679c\u8fdb\u884c\u96c6\u6210\u3002<\/p>\n\n\n\n


                \u4f7f\u7528Top-1\u63d0\u793a\u663e\u8457\u4f18\u4e8eInitial\uff08\u5373\u6ca1\u6709\u4f18\u5316\u7684\u63d0\u793a\uff09\uff0c\u8bc1\u660e\u63d0\u793a\u4f18\u5316\u8fc7\u7a0b\u5bf9\u4e8e\u63d0\u9ad8\u63a8\u8350\u6548\u679c\u81f3\u5173\u91cd\u8981\u3002
                Ensemble\u65b9\u6cd5\uff08EnSame\u548cEnCross\uff09\u672a\u80fd\u663e\u8457\u63d0\u5347\u6027\u80fd\uff0c\u53cd\u800c\u7a0d\u5fae\u964d\u4f4e\u4e86\u6548\u679c\uff0c\u8868\u660e\u7b80\u5355\u7684\u63d0\u793a\u96c6\u6210\u53ef\u80fd\u5e76\u4e0d\u80fd\u6709\u6548\u6539\u5584\u7ed3\u679c\uff0c\u4e14\u53ef\u80fd\u4f1a\u5f15\u5165\u566a\u58f0\u3002<\/p>\n\n\n\n

                \u603b\u7ed3\u4e0e\u7efc\u5408\u5bf9\u5176\u601d\u8003<\/h2>\n\n\n\n

                \uff08\u4e00\uff09\u8bba\u6587\u6838\u5fc3\u5185\u5bb9
                \u591a\u91cd\u610f\u56fe\u5efa\u6a21\uff1a\u63d0\u51fa\u4e86\u5229\u7528LLM\u5904\u7406\u7528\u6237\u5728\u540c\u4e00\u4f1a\u8bdd\u4e2d\u7684\u591a\u4e2a\u610f\u56fe\uff0c\u6253\u7834\u4e86\u4f20\u7edf\u4f1a\u8bdd\u63a8\u8350\u7cfb\u7edf\u4ec5\u5904\u7406\u5355\u4e00\u610f\u56fe\u7684\u9650\u5236\u3002
                \u7cbe\u7ec6\u8bbe\u8ba1\u63d0\u793a\u673a\u5236\uff1a\u901a\u8fc7\u63d0\u793a\u521d\u59cb\u5316\u3001\u4f18\u5316\u548c\u9009\u62e9\uff0c\u8bbe\u8ba1\u4e86\u4e00\u79cd\u52a8\u6001\u8c03\u6574\u63d0\u793a\u7684\u65b9\u5f0f\uff0c\u5e2e\u52a9LLM\u66f4\u597d\u5730\u7406\u89e3\u548c\u63a8\u7406\u7528\u6237\u7684\u591a\u91cd\u610f\u56fe\u3002\u91c7\u7528\u4e86UCB Bandits\u7b97\u6cd5\u6765\u9ad8\u6548\u4f18\u5316\u548c\u8bc4\u4f30\u63d0\u793a\uff0c\u4f7f\u5f97\u7cfb\u7edf\u80fd\u591f\u5e73\u8861\u201c\u63a2\u7d22\u201d\u548c\u201c\u5229\u7528\u201d\uff0c\u4e0d\u65ad\u9009\u62e9\u6700\u4f18\u7684\u63d0\u793a\u3002<\/p>\n\n\n\n

                \uff08\u4e8c\uff09\u7efc\u5408\u5bf9\u5176\u601d\u8003
                \u52a8\u6001\u591a\u610f\u56fe\u5efa\u6a21\uff1aLLM4ISR \u901a\u8fc7LLM\u5728\u8bed\u4e49\u5c42\u9762\u52a8\u6001\u8bc6\u522b\u7528\u6237\u610f\u56fe\uff0c\u65e0\u9700\u9884\u8bbe\u56fa\u5b9a\u610f\u56fe\u6570\u91cf\u3002\u540c\u7406\uff0c\u53ef\u4ee5\u66ff\u6362\u539f\u6709\u7684\u56fe\u8c31\u63a8\u7406\u601d\u8def\uff0c\u5c06\u6846\u67b6\u4e2d\u7684\u201c\u7c7b\u522b\u56fe\u8c31\u8f85\u52a9\u63a8\u7406\u201d\u8f6c\u6362\u4e3a LLM\u8bed\u4e49\u610f\u56fe\u89e3\u6790\u5668\uff0c\u6bd4\u5982\u76f4\u63a5\u7ed9\u5b9a\u7528\u6237\u5386\u53f2\u884c\u4e3a\u5e8f\u5217\u63a8\u6d4b\u51fa\u6f5c\u5728\u7684\u65b0\u610f\u56fe\u3002
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