{"id":3150,"date":"2026-01-26T04:33:18","date_gmt":"2026-01-26T04:33:18","guid":{"rendered":"https:\/\/umaax.com\/airuheshixianziranyuyanchulinlpyiwenkandong\/"},"modified":"2026-01-26T04:33:18","modified_gmt":"2026-01-26T04:33:18","slug":"airuheshixianziranyuyanchulinlpyiwenkandong","status":"publish","type":"post","link":"https:\/\/umaax.com\/en\/airuheshixianziranyuyanchulinlpyiwenkandong\/","title":{"rendered":"AI\u5982\u4f55\u5b9e\u73b0\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff08NLP\uff09\uff1f\u4e00\u6587\u770b\u61c2"},"content":{"rendered":"

\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff08NLP\uff09\u662f\u4eba\u5de5\u667a\u80fd\u7684\u4e00\u4e2a\u5206\u652f\uff0c\u8ba9\u8ba1\u7b97\u673a\u80fd\u7406\u89e3\u3001\u89e3\u91ca\u548c\u751f\u6210\u4eba\u7c7b\u8bed\u8a00\u3002\u901a\u8fc7\u4e00\u7cfb\u5217\u6280\u672f\uff0c\u5982\u5206\u8bcd\u3001\u8bcd\u6027\u6807\u6ce8\u3001\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u3001\u8bcd\u5d4c\u5165\u3001\u673a\u5668\u7ffb\u8bd1\u548c\u60c5\u611f\u5206\u6790\u7b49\uff0c\u7ed3\u5408\u4ece\u4f20\u7edf\u7edf\u8ba1\u65b9\u6cd5\u5230\u73b0\u4ee3\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\uff08\u5982BERT\u3001GPT\u7cfb\u5217\u548c\u5927\u578b\u8bed\u8a00\u6a21\u578bLLMs\uff09\u7684\u7b97\u6cd5\uff0c\u5b9e\u73b0\u4e0e\u4eba\u7c7b\u8bed\u8a00\u7684\u4ea4\u4e92\u3002<\/p>\n

\"\" <\/p>\n

\u4ec0\u4e48\u662f\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff1f<\/h2>\n

\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff08Natural Language Processing, NLP\uff09\u662f\u4eba\u5de5\u667a\u80fd\uff08AI\uff09\u548c\u8ba1\u7b97\u673a\u79d1\u5b66\u9886\u57df\u7684\u4e00\u4e2a\u5173\u952e\u5206\u652f\uff0c\u6838\u5fc3\u76ee\u6807\u662f\u8ba9\u8ba1\u7b97\u673a\u80fd\u7406\u89e3\u3001\u89e3\u91ca\u3001\u64cd\u4f5c\u5e76\u6700\u7ec8\u751f\u6210\u4eba\u7c7b\u8bed\u8a00\u3002<\/p>\n

\u6253\u7834\u4eba\u4e0e\u673a\u5668\u4e4b\u95f4\u7684\u8bed\u8a00\u969c\u788d\uff0c\u4f7f\u8ba1\u7b97\u673a\u80fd\u50cf\u4eba\u7c7b\u4e00\u6837\u5904\u7406\u548c\u5206\u6790\u6211\u4eec\u6240\u4f7f\u7528\u7684\u8bed\u8a00\uff0c\u65e0\u8bba\u662f\u6587\u672c\u8fd8\u662f\u8bed\u97f3 \u3002NLP\u6280\u672f\u901a\u8fc7\u7ed3\u5408\u8ba1\u7b97\u8bed\u8a00\u5b66\uff08\u57fa\u4e8e\u89c4\u5219\u7684\u4eba\u7c7b\u8bed\u8a00\u5efa\u6a21\uff09\u4e0e\u7edf\u8ba1\u5efa\u6a21\u3001\u673a\u5668\u5b66\u4e60\uff08ML\uff09\u4ee5\u53ca\u6df1\u5ea6\u5b66\u4e60\u7b49\u65b9\u6cd5\uff0c\u4f7f\u8ba1\u7b97\u673a\u548c\u6570\u5b57\u8bbe\u5907\u80fd\u8bc6\u522b\u3001\u7406\u89e3\u6587\u672c\u548c\u8bed\u97f3\u7684\u542b\u4e49\uff0c\u751f\u6210\u81ea\u7136\u7684\u8bed\u8a00\u8f93\u51fa\u3002<\/p>\n

\u4f8b\u5982\u641c\u7d22\u5f15\u64ce\u7684\u667a\u80fd\u63d0\u793a\u3001\u667a\u80fd\u8bed\u97f3\u52a9\u624b\uff08\u5982Siri\u3001Alexa\uff09\u3001\u673a\u5668\u7ffb\u8bd1\u3001\u667a\u80fd\u5ba2\u670d\u7b49\uff0c\u90fd\u79bb\u4e0d\u5f00NLP\u7684\u652f\u6301\u3002NLP\u7684\u7814\u7a76\u4e5f\u63a8\u52a8\u4e86\u751f\u6210\u5f0fAI\u65f6\u4ee3\u7684\u5230\u6765\uff0c\u4f7f\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08LLM\uff09\u80fd\u8fdb\u884c\u6d41\u7545\u7684\u4ea4\u6d41\uff0c\u56fe\u50cf\u751f\u6210\u6a21\u578b\u4e5f\u80fd\u7406\u89e3\u6587\u672c\u8bf7\u6c42\u3002<\/p>\n

NLP\u7684\u7814\u7a76\u8303\u56f4\u6db5\u76d6\u4e86\u4ece\u57fa\u7840\u7684\u6587\u672c\u5206\u6790\u3001\u4fe1\u606f\u62bd\u53d6\uff0c\u5230\u66f4\u9ad8\u7ea7\u7684\u673a\u5668\u7ffb\u8bd1\u3001\u95ee\u7b54\u7cfb\u7edf\u7b49\u591a\u4e2a\u65b9\u9762 \u3002\u5173\u6ce8\u5982\u4f55\u8ba9\u8ba1\u7b97\u673a\u201c\u8bfb\u61c2\u201d\u6587\u5b57\uff0c\u5982\u4f55\u8ba9\u8ba1\u7b97\u673a\u7406\u89e3\u6587\u5b57\u80cc\u540e\u7684\u542b\u4e49\u3001\u60c5\u611f\u548c\u610f\u56fe \u3002\u4f8b\u5982\uff0c\u5728\u667a\u80fd\u5ba2\u670d\u573a\u666f\u4e2d\uff0cNLP\u6280\u672f\u9700\u8981\u7406\u89e3\u7528\u6237\u63d0\u51fa\u7684\u95ee\u9898\uff0c\u5206\u6790\u5176\u60c5\u7eea\uff0c\u7ed9\u51fa\u6070\u5f53\u7684\u56de\u590d\u3002\u5728\u673a\u5668\u7ffb\u8bd1\u4e2d\uff0cNLP\u9700\u8981\u7406\u89e3\u6e90\u8bed\u8a00\u7684\u53e5\u5b50\u7ed3\u6784\u548c\u8bed\u4e49\uff0c\u5c06\u51c6\u786e\u5730\u8f6c\u6362\u6210\u76ee\u6807\u8bed\u8a00\u3002<\/p>\n

\n

NLP\u7684\u6838\u5fc3\u4f18\u52bf\u4e0d\u4ec5\u5728\u4e8e\u7b80\u5355\u7684\u6587\u672c\u89e3\u6790\uff0c\u66f4\u5728\u4e8e\u5bf9\u8bed\u5883\u3001\u8bed\u4e49\u3001\u60c5\u611f\u7b49\u590d\u6742\u56e0\u7d20\u7684\u7efc\u5408\u628a\u63e1\uff0c\u76ee\u6807\u662f\u8ba9\u8ba1\u7b97\u673a\u80fd\u771f\u6b63\u7406\u89e3\u3001\u89e3\u91ca\u548c\u751f\u6210\u4eba\u7c7b\u8bed\u8a00\uff0c\u5b9e\u73b0\u66f4\u81ea\u7136\u3001\u66f4\u6709\u6548\u7684\u6c9f\u901a\u3002<\/p>\n<\/blockquote>\n

NLP\u7684\u6838\u5fc3\u6982\u5ff5\uff1a\u7406\u89e3\u8bed\u8a00\u7684\u4e0d\u540c\u5c42\u9762<\/h2>\n

\u8bcd\u6cd5\u5206\u6790\uff1a\u4ece\u5355\u8bcd\u5165\u624b<\/strong><\/h4>\n

\u8bcd\u6cd5\u5206\u6790\uff08Lexical Analysis\uff09\u662fNLP\u7684\u57fa\u77f3\uff0c\u4e3b\u8981\u5173\u6ce8\u6587\u672c\u4e2d\u6700\u57fa\u672c\u7684\u5355\u4f4d\u2014\u2014\u8bcd\uff08Word\uff09\u6216\u8bcd\u7d20\uff08Morpheme\uff09\u3002\u6838\u5fc3\u4efb\u52a1\u662f\u5c06\u8fde\u7eed\u7684\u6587\u672c\u6d41\u5207\u5206\u6210\u5177\u6709\u72ec\u7acb\u610f\u4e49\u7684\u57fa\u672c\u5355\u5143\uff0c\u5373\u201c\u8bcd\u5143\u201d\uff08Token\uff09\uff0c\u8bc6\u522b\u8fd9\u4e9b\u8bcd\u5143\u7684\u5c5e\u6027\u3002\u8fd9\u4e2a\u8fc7\u7a0b\u88ab\u79f0\u4e3a\u5206\u8bcd\uff08Tokenization\uff09<\/strong>\u3002<\/p>\n

\n

\u4f8b\u5982\uff0c\u5bf9\u4e8e\u82f1\u6587\u53e5\u5b50 \u201cI love NLP!\u201d\uff0c\u5206\u8bcd\u540e\u4f1a\u5f97\u5230 [\u201cI\u201d, \u201clove\u201d, \u201cNLP\u201d, \u201c!\u201d]\u3002\u5bf9\u4e8e\u4e2d\u6587\u8fd9\u7c7b\u6ca1\u6709\u660e\u663e\u7a7a\u683c\u5206\u9694\u7684\u8bed\u8a00\uff0c\u5206\u8bcd\u5219\u66f4\u4e3a\u590d\u6742\uff0c\u4f8b\u5982\u53e5\u5b50\u201c\u6211\u7231\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff01\u201d\u53ef\u80fd\u9700\u8981\u88ab\u5206\u89e3\u4e3a [\u201c\u6211\u201d, \u201c\u7231\u201d, \u201c\u81ea\u7136\u8bed\u8a00\u5904\u7406\u201d, \u201c\uff01\u201d] \u3002\u5206\u8bcd\u7684\u51c6\u786e\u6027\u76f4\u63a5\u5f71\u54cd\u540e\u7eedNLP\u4efb\u52a1\u7684\u6548\u679c<\/strong>\u3002<\/p>\n<\/blockquote>\n

\u8bcd\u6cd5\u5206\u6790\u8fd8\u5305\u62ec\u8bcd\u5f62\u8fd8\u539f\uff08Lemmatization\uff09\u548c\u8bcd\u5e72\u63d0\u53d6\uff08Stemming\uff09<\/strong>\u3002<\/p>\n

\u8bcd\u5f62\u8fd8\u539f\uff1a<\/strong>\u662f\u5c06\u5355\u8bcd\u7684\u5404\u79cd\u5c48\u6298\u5f62\u5f0f\uff08\u5982\u590d\u6570\u3001\u8fc7\u53bb\u5f0f\u3001\u6bd4\u8f83\u7ea7\u7b49\uff09\u8fd8\u539f\u4e3a\u5176\u57fa\u672c\u5f62\u5f0f\uff08\u8bcd\u5143\uff09\uff0c\u4f8b\u5982\u5c06 \u201crunning\u201d \u8fd8\u539f\u4e3a \u201crun\u201d\uff0c\u5c06 \u201cbetter\u201d \u8fd8\u539f\u4e3a \u201cgood\u201d\u3002<\/p>\n

\u8bcd\u5e72\u63d0\u53d6\uff1a<\/strong>\u662f\u901a\u8fc7\u53bb\u9664\u5355\u8bcd\u7684\u524d\u540e\u7f00\u6765\u5f97\u5230\u8bcd\u5e72\uff0c\u4f8b\u5982\u5c06 \u201chappiness\u201d \u63d0\u53d6\u4e3a \u201chappi\u201d\u3002\u867d\u7136\u8bcd\u5e72\u63d0\u53d6\u5f97\u5230\u7684\u7ed3\u679c\u53ef\u80fd\u4e0d\u662f\u4e00\u4e2a\u6709\u6548\u7684\u5355\u8bcd\uff0c\u4f46\u6709\u52a9\u4e8e\u5c06\u5177\u6709\u76f8\u540c\u8bcd\u6839\u7684\u8bcd\u6c47\u5f52\u4e3a\u4e00\u7c7b\u3002\u8fd9\u4e9b\u6280\u672f\u6709\u52a9\u4e8e\u89c4\u8303\u5316\u6587\u672c\u6570\u636e\uff0c\u51cf\u5c11\u8bcd\u6c47\u7684\u591a\u6837\u6027\uff0c\u7b80\u5316\u540e\u7eed\u7684\u5206\u6790\u548c\u5904\u7406 \u3002<\/p>\n

\u8bcd\u6027\u6807\u6ce8\uff08Part-of-Speech Tagging, POS Tagging\uff09\uff1a<\/strong>\u4e5f\u662f\u8bcd\u6cd5\u5206\u6790\u7684\u91cd\u8981\u7ec4\u6210\u90e8\u5206\uff0c\u4e3a\u53e5\u5b50\u4e2d\u7684\u6bcf\u4e2a\u8bcd\u5143\u6807\u6ce8\u5176\u8bed\u6cd5\u7c7b\u522b\uff0c\u5982\u540d\u8bcd\uff08noun\uff09\u3001\u52a8\u8bcd\uff08verb\uff09\u3001\u5f62\u5bb9\u8bcd\uff08adjective\uff09\u3001\u526f\u8bcd\uff08adverb\uff09\u7b49 \u3002\u4f8b\u5982\uff0c\u5728\u53e5\u5b50 \u201cThe quick brown fox jumps over the lazy dog\u201d \u4e2d\uff0c\u201dfox\u201d \u4f1a\u88ab\u6807\u6ce8\u4e3a\u540d\u8bcd\uff0c\u201djumps\u201d \u4f1a\u88ab\u6807\u6ce8\u4e3a\u52a8\u8bcd\u3002\u8bcd\u6027\u6807\u6ce8\u5bf9\u4e8e\u7406\u89e3\u53e5\u5b50\u7ed3\u6784\u81f3\u5173\u91cd\u8981\uff0c\u662f\u8bb8\u591aNLP\u4efb\u52a1\uff08\u5982\u53e5\u6cd5\u5206\u6790\u3001\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u3001\u673a\u5668\u7ffb\u8bd1\u548c\u60c5\u611f\u5206\u6790\uff09\u7684\u57fa\u7840 \u3002<\/p>\n

\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\uff08Named Entity Recognition, NER\uff09\uff1a<\/strong>\u4e5f\u662f\u8bcd\u6cd5\u5206\u6790\u7684\u4e00\u90e8\u5206\uff0c\u76ee\u6807\u662f\u8bc6\u522b\u6587\u672c\u4e2d\u5177\u6709\u7279\u5b9a\u610f\u4e49\u7684\u5b9e\u4f53\uff0c\u5982\u4eba\u540d\u3001\u5730\u540d\u3001\u7ec4\u7ec7\u673a\u6784\u540d\u3001\u65e5\u671f\u3001\u65f6\u95f4\u3001\u8d27\u5e01\u7b49\uff0c\u5c06\u5176\u5f52\u7c7b\u5230\u9884\u5b9a\u4e49\u7684\u7c7b\u522b\u4e2d \u3002\u4f8b\u5982\uff0c\u5728\u53e5\u5b50\u201c\u82f9\u679c\u516c\u53f8\u4e8e1976\u5e744\u67081\u65e5\u7531\u53f2\u8482\u592b\u00b7\u4e54\u5e03\u65af\u521b\u7acb\u201d\u4e2d\uff0c\u201c\u82f9\u679c\u516c\u53f8\u201d\u662f\u7ec4\u7ec7\u673a\u6784\u540d\uff0c\u201c1976\u5e744\u67081\u65e5\u201d\u662f\u65e5\u671f\uff0c\u201c\u53f2\u8482\u592b\u00b7\u4e54\u5e03\u65af\u201d\u662f\u4eba\u540d\u3002\u51c6\u786e\u7684\u5206\u8bcd\u548c\u8bcd\u6027\u6807\u6ce8\u662f\u540e\u7eed\u66f4\u9ad8\u7ea7NLP\u4efb\u52a1\u6210\u529f\u7684\u5173\u952e\u3002<\/p>\n

\"\" <\/p>\n

\u53e5\u6cd5\u5206\u6790\uff1a\u7406\u89e3\u53e5\u5b50\u7ed3\u6784<\/strong><\/h4>\n

\u53e5\u6cd5\u5206\u6790\uff08Syntactic Analysis\uff09\uff0c\u4e5f\u79f0\u4e3a\u53e5\u6cd5\u89e3\u6790\uff08Parsing\uff09\uff0c\u662f\u5728\u8bcd\u6cd5\u5206\u6790\u7684\u57fa\u7840\u4e0a\uff0c\u8fdb\u4e00\u6b65\u5206\u6790\u53e5\u5b50\u7684\u8bed\u6cd5\u7ed3\u6784\uff0c\u786e\u5b9a\u53e5\u5b50\u4e2d\u5404\u4e2a\u7ec4\u6210\u90e8\u5206\u4e4b\u95f4\u7684\u5173\u7cfb\u4ee5\u53ca\u5b83\u4eec\u5982\u4f55\u7ec4\u5408\u6210\u4e00\u4e2a\u6709\u610f\u4e49\u7684\u6574\u4f53\u3002\u53e5\u6cd5\u5206\u6790\u7684\u76ee\u7684\u662f\u6784\u5efa\u53e5\u5b50\u7684\u53e5\u6cd5\u6811\uff08Parse Tree\uff09\u6216\u4f9d\u5b58\u5173\u7cfb\u56fe\uff08Dependency Graph\uff09<\/strong>\uff0c\u6e05\u6670\u5730\u5c55\u793a\u51fa\u53e5\u5b50\u7684\u4e3b\u8c13\u5bbe\u3001\u5b9a\u72b6\u8865\u7b49\u6210\u5206\u4ee5\u53ca\u5b83\u4eec\u4e4b\u95f4\u7684\u4fee\u9970\u5173\u7cfb\u6216\u4f9d\u5b58\u5173\u7cfb\u3002<\/p>\n

\n

\u4f8b\u5982\uff0c\u5bf9\u4e8e\u53e5\u5b50 \u201cThe cat sat on the mat\u201d\uff0c\u53e5\u6cd5\u5206\u6790\u53ef\u4ee5\u8bc6\u522b\u51fa\u4e3b\u8bed\u662f \u201cThe cat\u201d\uff0c\u8c13\u8bed\u662f \u201csat\u201d\uff0c\u201don the mat\u201d \u662f\u8868\u793a\u5730\u70b9\u7684\u72b6\u8bed\u3002<\/p>\n<\/blockquote>\n

\u7406\u89e3\u53e5\u6cd5\u7ed3\u6784\u5bf9\u4e8e\u51c6\u786e\u7406\u89e3\u53e5\u5b50\u542b\u4e49\u81f3\u5173\u91cd\u8981\uff0c\u5728\u5904\u7406\u590d\u6742\u957f\u53e5\u65f6\u3002\u53e5\u6cd5\u5206\u6790\u7684\u7ed3\u679c\u53ef\u4ee5\u7528\u4e8e\u591a\u79cdNLP\u5e94\u7528\uff0c\u5982\u673a\u5668\u7ffb\u8bd1\uff08\u5e2e\u52a9\u8c03\u6574\u76ee\u6807\u8bed\u8a00\u7684\u8bed\u5e8f\uff09\u3001\u4fe1\u606f\u62bd\u53d6\uff08\u8bc6\u522b\u5b9e\u4f53\u95f4\u7684\u5173\u7cfb\uff09\u3001\u95ee\u7b54\u7cfb\u7edf\uff08\u7406\u89e3\u95ee\u9898\u7684\u7ed3\u6784\uff09\u7b49\u3002<\/p>\n

\u53e5\u6cd5\u5206\u6790\u5206\u4e3a\u4e24\u79cd\u4e3b\u8981\u7c7b\u578b\uff1a\u6210\u5206\u53e5\u6cd5\u5206\u6790\uff08Constituency Parsing\uff09\u548c\u4f9d\u5b58\u53e5\u6cd5\u5206\u6790\uff08Dependency Parsing\uff09<\/strong>\u3002<\/p>\n

\u6210\u5206\u53e5\u6cd5\u5206\u6790\uff1a<\/strong>\u5173\u6ce8\u5982\u4f55\u5c06\u53e5\u5b50\u5206\u89e3\u4e3a\u4e00\u7cfb\u5217\u77ed\u8bed\u7ed3\u6784\uff0c\u4f8b\u5982\u540d\u8bcd\u77ed\u8bed\uff08NP\uff09\u3001\u52a8\u8bcd\u77ed\u8bed\uff08VP\uff09\u7b49\uff0c\u6700\u7ec8\u5f62\u6210\u4e00\u68f5\u6811\u72b6\u7ed3\u6784\u3002<\/p>\n

\u4f9d\u5b58\u53e5\u6cd5\u5206\u6790\uff1a<\/strong>\u5173\u6ce8\u53e5\u5b50\u4e2d\u8bcd\u4e0e\u8bcd\u4e4b\u95f4\u7684\u4f9d\u5b58\u5173\u7cfb\uff0c\u4f8b\u5982\u54ea\u4e2a\u8bcd\u662f\u6838\u5fc3\u52a8\u8bcd\uff0c\u54ea\u4e9b\u8bcd\u662f\u5b83\u7684\u4e3b\u8bed\u3001\u5bbe\u8bed\u6216\u4fee\u9970\u8bed \u3002\u4f8b\u5982\uff0c\u5728\u53e5\u5b50 \u201cShe bought a red car\u201d \u4e2d\uff0c\u201dbought\u201d \u662f\u6838\u5fc3\u52a8\u8bcd\uff0c\u201dShe\u201d \u662f\u4e3b\u8bed\uff0c\u201dcar\u201d \u662f\u5bbe\u8bed\uff0c\u201dred\u201d \u4fee\u9970 \u201ccar\u201d\u3002<\/p>\n

\u53e5\u6cd5\u5206\u6790\u662fNLP\u4e2d\u7684\u4e00\u4e2a\u6838\u5fc3\u4e14\u5177\u6709\u6311\u6218\u6027\u7684\u4efb\u52a1\uff0c\u5728\u5904\u7406\u6b67\u4e49\u53e5\uff08\u5373\u4e00\u4e2a\u53e5\u5b50\u53ef\u80fd\u6709\u591a\u79cd\u5408\u6cd5\u7684\u53e5\u6cd5\u7ed3\u6784\uff09\u65f6\u3002\u8fd1\u5e74\u6765\uff0c\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u53e5\u6cd5\u5206\u6790\u65b9\u6cd5\u53d6\u5f97\u4e86\u663e\u8457\u8fdb\u5c55\uff0c\u80fd\u66f4\u51c6\u786e\u5730\u5206\u6790\u53e5\u5b50\u7ed3\u6784\u3002<\/p>\n

\"\" <\/p>\n

\u8bed\u4e49\u5206\u6790\uff1a\u63a2\u7a76\u8bed\u8a00\u7684\u542b\u4e49<\/strong><\/h4>\n

\u8bed\u4e49\u5206\u6790\uff08Semantic Analysis\uff09\u662f\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e2d\u66f4\u4e3a\u6df1\u5165\u7684\u4e00\u4e2a\u5c42\u9762\uff0c\u63a2\u7a76\u8bed\u8a00\u6240\u8868\u8fbe\u7684\u771f\u5b9e\u542b\u4e49\uff0c\u4e0d\u4ec5\u662f\u8868\u9762\u7684\u8bcd\u6c47\u548c\u53e5\u6cd5\u7ed3\u6784\u3002\u5982\u679c\u8bf4\u53e5\u6cd5\u5206\u6790\u662f\u7406\u89e3\u53e5\u5b50\u7684\u201c\u9aa8\u67b6\u201d\uff0c\u90a3\u8bed\u4e49\u5206\u6790\u5c31\u662f\u7406\u89e3\u53e5\u5b50\u7684\u201c\u8840\u8089\u201d\u548c\u201c\u7075\u9b42\u201d\u3002<\/p>\n

\u8bed\u4e49\u5206\u6790\u7684\u76ee\u6807\u662f\u5c06\u6587\u672c\u8f6c\u6362\u4e3a\u7ed3\u6784\u5316\u7684\u4fe1\u606f\uff0c\u6d89\u53ca\u5230\u8bcd\u4e49\u3001\u8bed\u6cd5\u7ed3\u6784\u3001\u8bed\u5883\u7b49\u591a\u4e2a\u65b9\u9762 \u3002\u8bd5\u56fe\u56de\u7b54\u201c\u8fd9\u4e2a\u53e5\u5b50\u5230\u5e95\u662f\u4ec0\u4e48\u610f\u601d\uff1f\u201d\u4ee5\u53ca\u201c\u8fd9\u4e2a\u53e5\u5b50\u8868\u8fbe\u4e86\u4ec0\u4e48\u547d\u9898\uff1f\u201d\u7b49\u95ee\u9898\u3002\u4f8b\u5982\uff0c\u53e5\u5b50 \u201cThe bank is closed\u201d \u4e2d\u7684 \u201cbank\u201d \u53ef\u4ee5\u6307\u91d1\u878d\u673a\u6784\uff0c\u4e5f\u53ef\u4ee5\u6307\u6cb3\u5cb8\uff0c\u8bed\u4e49\u5206\u6790\u9700\u8981\u6839\u636e\u4e0a\u4e0b\u6587\u6765\u786e\u5b9a\u5176\u786e\u5207\u542b\u4e49\u3002\u540c\u6837\uff0c\u53e5\u5b50 \u201cFlying planes can be dangerous\u201d \u4e5f\u6709\u4e24\u79cd\u53ef\u80fd\u7684\u89e3\u91ca\uff1a\u201c\u9a7e\u9a76\u98de\u673a\u53ef\u80fd\u662f\u5371\u9669\u7684\u201d\u6216\u201c\u6b63\u5728\u98de\u7684\u98de\u673a\u53ef\u80fd\u662f\u5371\u9669\u7684\u201d\uff0c\u8bed\u4e49\u5206\u6790\u9700\u8981\u89e3\u51b3\u8fd9\u79cd\u6b67\u4e49\u3002<\/p>\n

\n

\u8bed\u4e49\u6b67\u4e49\u793a\u4f8b<\/span><\/p>\n

\u53e5\u5b50 \u201cThe bank is closed\u201d \u4e2d\u7684 \u201cbank\u201d \u53ef\u4ee5\u6307\uff1a<\/p>\n

    \n
  • \u91d1\u878d\u673a\u6784\uff08\u94f6\u884c\uff09<\/li>\n
  • \u6cb3\u5cb8\uff08\u6cb3\u5824\uff09<\/li>\n<\/ul>\n

    \u8bed\u4e49\u5206\u6790\u9700\u8981\u6839\u636e\u4e0a\u4e0b\u6587\u6765\u786e\u5b9a\u5176\u786e\u5207\u542b\u4e49\u3002<\/p>\n<\/blockquote>\n

    \u8bed\u4e49\u5206\u6790\u5305\u542b\u591a\u4e2a\u5b50\u4efb\u52a1\uff1a<\/p>\n

      \n
    • \u8bcd\u4e49\u6d88\u6b67\uff08Word Sense Disambiguation, WSD\uff09<\/strong>\uff0c\u5373\u786e\u5b9a\u4e00\u4e2a\u8bcd\u5728\u7279\u5b9a\u4e0a\u4e0b\u6587\u4e2d\u7684\u51c6\u786e\u542b\u4e49 \u3002<\/li>\n
    • \u8bed\u4e49\u89d2\u8272\u6807\u6ce8\uff08Semantic Role Labeling, SRL\uff09<\/strong>\u662f\u53e6\u4e00\u4e2a\u91cd\u8981\u7684\u8bed\u4e49\u5206\u6790\u4efb\u52a1\uff0c\u8bc6\u522b\u53e5\u5b50\u4e2d\u8c13\u8bcd\uff08\u901a\u5e38\u662f\u52a8\u8bcd\uff09\u53ca\u5176\u76f8\u5173\u7684\u8bed\u4e49\u89d2\u8272\uff0c\u5982\u65bd\u4e8b\u8005\uff08Agent\uff09\u3001\u53d7\u4e8b\u8005\uff08Patient\uff09\u3001\u5de5\u5177\uff08Instrument\uff09\u3001\u5730\u70b9\uff08Location\uff09\u7b49 \u3002<\/li>\n
    • \n
      \n

      \u4f8b\u5982\uff0c\u5728\u53e5\u5b50 \u201cJohn gave Mary a book in the library\u201d \u4e2d\uff0c\u5bf9\u4e8e\u8c13\u8bcd \u201cgave\u201d\uff0c\u201dJohn\u201d \u662f\u65bd\u4e8b\u8005\uff0c\u201dMary\u201d \u662f\u63a5\u53d7\u8005\uff08Recipient\uff09\uff0c\u201da book\u201d \u662f\u53d7\u4e8b\u8005\uff0c\u201din the library\u201d \u662f\u5730\u70b9\u3002\u901a\u8fc7\u8bed\u4e49\u89d2\u8272\u6807\u6ce8\uff0c\u53ef\u4ee5\u66f4\u6df1\u5165\u5730\u7406\u89e3\u53e5\u5b50\u6240\u63cf\u8ff0\u7684\u4e8b\u4ef6\u6216\u72b6\u6001\u3002<\/p>\n<\/blockquote>\n<\/li>\n

    • \u8bed\u4e49\u5206\u6790\u8fd8\u6d89\u53ca\u5230\u8bed\u4e49\u5173\u7cfb\u62bd\u53d6<\/strong>\u3001\u6587\u672c\u8574\u542b\u8bc6\u522b\uff08Textual Entailment\uff09<\/strong>\u7b49\u4efb\u52a1\u3002<\/li>\n
    • \u8bcd\u5d4c\u5165\uff08Word Embedding\uff09\u6280\u672f<\/strong>\uff0c\u5982Word2Vec\u548cGloVe\uff0c\u80fd\u5c06\u8bcd\u8bed\u8868\u793a\u4e3a\u7a20\u5bc6\u7684\u5411\u91cf\uff0c\u6355\u6349\u8bcd\u8bed\u4e4b\u95f4\u7684\u8bed\u4e49\u76f8\u4f3c\u6027\uff0c\u4e3a\u8bed\u4e49\u5206\u6790\u63d0\u4f9b\u4e86\u6709\u529b\u7684\u5de5\u5177 \u3002\u5b9e\u73b0\u51c6\u786e\u7684\u8bed\u4e49\u5206\u6790\u662fNLP\u9886\u57df\u7684\u4e00\u5927\u6311\u6218\uff0c\u56e0\u4e3a\u5b83\u4e0d\u4ec5\u9700\u8981\u8bed\u8a00\u77e5\u8bc6\uff0c\u8fd8\u9700\u8981\u5927\u91cf\u7684\u4e16\u754c\u77e5\u8bc6\u548c\u5e38\u8bc6\u63a8\u7406\u80fd\u529b\u3002<\/li>\n<\/ul>\n

      \u8bed\u7528\u5206\u6790\uff1a\u7406\u89e3\u8bed\u8a00\u7684\u771f\u5b9e\u610f\u56fe<\/strong><\/h4>\n

      \u8bed\u7528\u5206\u6790\uff08Pragmatic Analysis\uff09\u662f\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e2d\u6700\u9ad8\u5c42\u6b21\u7684\u7406\u89e3\uff0c\u8d85\u8d8a\u4e86\u5b57\u9762\u610f\u4e49\u548c\u53e5\u5b50\u7ed3\u6784\uff0c\u63a2\u7a76\u8bed\u8a00\u5728\u7279\u5b9a\u8bed\u5883\u4e0b\u7684\u771f\u5b9e\u610f\u56fe\u3001\u9690\u542b\u610f\u4e49\u4ee5\u53ca\u8bf4\u8bdd\u8005\u548c\u542c\u8bdd\u8005\u4e4b\u95f4\u7684\u4e92\u52a8\u5173\u7cfb\u3002<\/p>\n

      \u8bed\u7528\u5206\u6790\u5173\u6ce8\u7684\u662f\u201c\u4e3a\u4ec0\u4e48\u8fd9\u4e48\u8bf4\uff1f\u201d\u4ee5\u53ca\u201c\u5728\u4ec0\u4e48\u60c5\u51b5\u4e0b\u8fd9\u4e48\u8bf4\uff1f\u201d\u3002\u4f8b\u5982\uff0c\u5f53\u6709\u4eba\u8bf4 \u201cIt\u2019s cold in here\u201d \u65f6\uff0c\u5176\u5b57\u9762\u610f\u601d\u662f\u63cf\u8ff0\u6e29\u5ea6\u4f4e\uff0c\u4f46\u5728\u7279\u5b9a\u8bed\u5883\u4e0b\uff0c\u8bed\u7528\u610f\u56fe\u53ef\u80fd\u662f\u8bf7\u6c42\u5173\u95ed\u7a97\u6237\u6216\u8c03\u9ad8\u6696\u6c14 \u3002\u53cd\u95ee\u53e5 \u201c\u96be\u9053\u4f60\u4e0d\u77e5\u9053\u5417\uff1f\u201d \u7684\u5b57\u9762\u610f\u601d\u662f\u8be2\u95ee\u5bf9\u65b9\u662f\u5426\u77e5\u9053\uff0c\u4f46\u8bed\u7528\u529f\u80fd\u5f80\u5f80\u662f\u8868\u8fbe\u80af\u5b9a\u6216\u8d23\u5907\u3002<\/p>\n

      \u8bed\u7528\u5206\u6790\u6d89\u53ca\u5230\u591a\u4e2a\u6982\u5ff5\uff1a<\/p>\n

        \n
      • \u8a00\u8bed\u884c\u4e3a\u7406\u8bba\uff08Speech Act Theory\uff09\uff1a<\/strong>\u8ba4\u4e3a\u8bf4\u8bdd\u672c\u8eab\u5c31\u662f\u4e00\u79cd\u884c\u4e3a\uff0c\u53ef\u4ee5\u5206\u4e3a\u9610\u8ff0\u7c7b\uff08assertives\uff09\u3001\u6307\u4ee4\u7c7b\uff08directives\uff09\u3001\u627f\u8bfa\u7c7b\uff08commissives\uff09\u3001\u8868\u8fbe\u7c7b\uff08expressives\uff09\u548c\u5ba3\u544a\u7c7b\uff08declarations\uff09\u7b49\u3002\u4f8b\u5982\uff0c\u201c\u6211\u4fdd\u8bc1\u660e\u5929\u5b8c\u6210\u201d\u662f\u4e00\u4e2a\u627f\u8bfa\u7c7b\u8a00\u8bed\u884c\u4e3a\u3002<\/li>\n
      • \u4f1a\u8bdd\u542b\u4e49\uff08Conversational Implicature\uff09\uff1a<\/strong>\u5373\u8bf4\u8bdd\u8005\u901a\u8fc7\u8fdd\u53cd\u5408\u4f5c\u539f\u5219\uff08Cooperative Principle\uff09\u7684\u67d0\u4e2a\u51c6\u5219\uff08\u5982\u6570\u91cf\u51c6\u5219\u3001\u8d28\u91cf\u51c6\u5219\u3001\u5173\u7cfb\u51c6\u5219\u3001\u65b9\u5f0f\u51c6\u5219\uff09\u6765\u95f4\u63a5\u8868\u8fbe\u67d0\u79cd\u542b\u4e49\u3002\u4f8b\u5982\uff0c\u5f53\u88ab\u95ee\u53ca\u5bf9\u67d0\u90e8\u7535\u5f71\u7684\u770b\u6cd5\u65f6\uff0c\u5982\u679c\u56de\u7b54 \u201cWell, the cinematography was good\u201d\uff0c\u53ef\u80fd\u6697\u793a\u4e86\u5bf9\u7535\u5f71\u5176\u4ed6\u65b9\u9762\u7684\u4e0d\u6ee1\u3002\u8bed\u7528\u5206\u6790\u9700\u8981\u8003\u8651\u4e0a\u4e0b\u6587\u4fe1\u606f\u3001\u8bf4\u8bdd\u8005\u548c\u542c\u8bdd\u8005\u7684\u80cc\u666f\u77e5\u8bc6\u3001\u793e\u4f1a\u6587\u5316\u56e0\u7d20\u7b49\u3002<\/li>\n
      • \u6307\u4ee3\u6d88\u89e3\uff08Anaphora Resolution\/Coreference Resolution\uff09\uff1a<\/strong>\u6d89\u53ca\u8bc6\u522b\u6587\u672c\u4e2d\u7684\u4ee3\u8bcd\u6216\u540d\u8bcd\u77ed\u8bed\uff08\u5982\u201c\u5b83\u201d\u3001\u201c\u4ed6\u4eec\u201d\u3001\u201c\u8fd9\u4e2a\u95ee\u9898\u201d\uff09\u5177\u4f53\u6307\u5411\u54ea\u4e2a\u5b9e\u4f53 \u3002\u7531\u4e8e\u8bed\u7528\u610f\u4e49\u7684\u590d\u6742\u6027\u548c\u9ad8\u5ea6\u8bed\u5883\u4f9d\u8d56\u6027\uff0c\u8bed\u7528\u5206\u6790\u662fNLP\u4e2d\u6781\u5177\u6311\u6218\u6027\u7684\u9886\u57df\uff0c\u76ee\u524d\u4ecd\u5904\u4e8e\u63a2\u7d22\u9636\u6bb5\u3002<\/li>\n<\/ul>\n

        AI\u5982\u4f55\u5b66\u4e60\u548c\u5904\u7406\u8bed\u8a00<\/h2>\n

        \u8fc7\u7a0b\u6d89\u53ca\u5230\u6570\u636e\u9884\u5904\u7406\u3001\u6587\u672c\u8868\u793a\u548c\u8bed\u8a00\u6a21\u578b\u7b49\u5173\u952e\u73af\u8282\u3002AI\u7cfb\u7edf\u901a\u8fc7\u5206\u6790\u6d77\u91cf\u7684\u6587\u672c\u8bed\u6599\uff0c\u5b66\u4e60\u8bcd\u6c47\u3001\u8bed\u6cd5\u3001\u8bed\u4e49\u4e43\u81f3\u8bed\u7528\u5c42\u9762\u7684\u77e5\u8bc6\uff0c\u80fd\u5904\u7406\u5404\u79cd\u590d\u6742\u7684\u8bed\u8a00\u4efb\u52a1\u3002<\/p>\n

        \u6587\u672c\u9884\u5904\u7406\uff1a\u4e3a\u5206\u6790\u505a\u597d\u51c6\u5907<\/strong><\/h4>\n

        \u6587\u672c\u9884\u5904\u7406\u662fNLP\u6d41\u7a0b\u4e2d\u7684\u7b2c\u4e00\u6b65\uff0c\u4e5f\u662f\u975e\u5e38\u5173\u952e\u7684\u4e00\u73af\uff0c\u76ee\u7684\u662f\u5c06\u539f\u59cb\u7684\u3001\u975e\u7ed3\u6784\u5316\u7684\u6587\u672c\u6570\u636e\u8f6c\u6362\u6210\u5e72\u51c0\u3001\u89c4\u6574\u7684\u683c\u5f0f\uff0c\u4ee5\u4fbf\u540e\u7eed\u7684NLP\u7b97\u6cd5\u66f4\u6709\u6548\u5730\u8fdb\u884c\u5206\u6790\u548c\u5b66\u4e60\u3002\u539f\u59cb\u6587\u672c\u6570\u636e\u5f80\u5f80\u5305\u542b\u5f88\u591a\u5bf9\u5206\u6790\u65e0\u76ca\u751a\u81f3\u4f1a\u4ea7\u751f\u5e72\u6270\u7684\u4fe1\u606f\uff0c\u4f8b\u5982HTML\u6807\u7b7e\u3001\u7279\u6b8a\u7b26\u53f7\u3001\u591a\u4f59\u7684\u7a7a\u683c\u3001\u62fc\u5199\u9519\u8bef\u3001\u505c\u7528\u8bcd\uff08stop words\uff09\u7b49\u3002\u6587\u672c\u9884\u5904\u7406\u5305\u62ec\u4ee5\u4e0b\u51e0\u4e2a\u4e3b\u8981\u6b65\u9aa4\uff1a<\/p>\n

          \n
        • \u6587\u672c\u6e05\u6d17\uff08Text Cleaning\uff09<\/strong>\uff1a\u53bb\u9664\u6587\u672c\u4e2d\u7684\u65e0\u5173\u5b57\u7b26\uff0c\u5982HTML\u6807\u7b7e\u3001\u63a7\u5236\u5b57\u7b26\u3001\u7279\u6b8a\u7b26\u53f7\u7b49\u3002\u5bf9\u4e8e\u67d0\u4e9b\u4efb\u52a1\uff0c\u53ef\u80fd\u8fd8\u9700\u8981\u5c06\u6587\u672c\u8f6c\u6362\u4e3a\u7edf\u4e00\u7684\u5927\u5c0f\u5199\u683c\u5f0f \u3002<\/li>\n
        • \u5206\u8bcd\uff08Tokenization\uff09<\/strong>\uff1a\u5c06\u8fde\u7eed\u7684\u6587\u672c\u5207\u5206\u6210\u72ec\u7acb\u7684\u8bcd\u5143\uff08tokens\uff09\uff0c\u5982\u5355\u8bcd\u3001\u6807\u70b9\u7b26\u53f7\u7b49\u3002\u5bf9\u4e8e\u4e2d\u6587\u7b49\u6ca1\u6709\u660e\u663e\u5206\u9694\u7b26\u7684\u8bed\u8a00\uff0c\u5206\u8bcd\u662f\u4e00\u4e2a\u66f4\u5177\u6311\u6218\u6027\u7684\u4efb\u52a1 \u3002<\/li>\n
        • \u53bb\u9664\u505c\u7528\u8bcd\uff08Stop Word Removal\uff09<\/strong>\uff1a\u505c\u7528\u8bcd\u662f\u6307\u5728\u6587\u672c\u4e2d\u9891\u7e41\u51fa\u73b0\u4f46\u5bf9\u8868\u8fbe\u6838\u5fc3\u8bed\u4e49\u8d21\u732e\u4e0d\u5927\u7684\u8bcd\u8bed\uff0c\u5982\u201c\u7684\u201d\u3001\u201c\u662f\u201d\u3001\u201c\u5728\u201d\u7b49\u51a0\u8bcd\u3001\u4ecb\u8bcd\u3001\u8fde\u8bcd\u3002\u53bb\u9664\u505c\u7528\u8bcd\u53ef\u4ee5\u51cf\u5c11\u7279\u5f81\u7a7a\u95f4\u7684\u7ef4\u5ea6\uff0c\u63d0\u9ad8\u6a21\u578b\u7684\u6548\u7387\u548c\u6027\u80fd \u3002<\/li>\n
        • \u8bcd\u5f62\u8fd8\u539f\uff08Lemmatization\uff09\u6216\u8bcd\u5e72\u63d0\u53d6\uff08Stemming\uff09<\/strong>\uff1a\u5c06\u8bcd\u8bed\u8fd8\u539f\u4e3a\u5176\u57fa\u672c\u5f62\u5f0f\u6216\u8bcd\u5e72\uff0c\u4ee5\u51cf\u5c11\u8bcd\u6c47\u7684\u591a\u6837\u6027\uff0c\u5e2e\u52a9\u6a21\u578b\u66f4\u597d\u5730\u8bc6\u522b\u8bcd\u4e49 \u3002\u4f8b\u5982\uff0c\u5c06\u201crunning\u201d\u8fd8\u539f\u4e3a\u201crun\u201d\u3002<\/li>\n
        • \u62fc\u5199\u7ea0\u9519\uff08Spell Correction\uff09<\/strong>\uff1a\u68c0\u6d4b\u5e76\u7ea0\u6b63\u6587\u672c\u4e2d\u7684\u62fc\u5199\u9519\u8bef\uff0c\u8fd9\u5bf9\u4e8e\u63d0\u9ad8\u540e\u7eed\u5206\u6790\u7684\u51c6\u786e\u6027\u975e\u5e38\u91cd\u8981\u3002<\/li>\n
        • \u6587\u672c\u89c4\u8303\u5316\uff08Text Normalization\uff09<\/strong>\uff1a\u5c06\u6587\u672c\u8f6c\u6362\u4e3a\u6807\u51c6\u683c\u5f0f\uff0c\u4f8b\u5982\u5c06\u6570\u5b57\u8f6c\u6362\u4e3a\u6587\u5b57\u8868\u793a\uff0c\u5c06\u7f29\u5199\u5c55\u5f00\u7b49\u3002<\/li>\n<\/ul>\n

          \u6587\u672c\u9884\u5904\u7406\u7684\u8d28\u91cf\u76f4\u63a5\u5f71\u54cd\u540e\u7eedNLP\u6a21\u578b\u7684\u6027\u80fd\u3002\u4e0d\u540c\u7684NLP\u4efb\u52a1\u548c\u5e94\u7528\u573a\u666f\u53ef\u80fd\u9700\u8981\u4e0d\u540c\u7684\u9884\u5904\u7406\u7b56\u7565\u3002<\/p>\n

          \n

          \u6587\u672c\u8868\u793a\uff1a\u5c06\u6587\u5b57\u8f6c\u5316\u4e3a\u673a\u5668\u53ef\u7406\u89e3\u7684\u5f62\u5f0f<\/strong><\/h4>\n

          \u5728\u8ba1\u7b97\u673a\u80fd\u5904\u7406\u81ea\u7136\u8bed\u8a00\u4e4b\u524d\uff0c\u5fc5\u987b\u5c06\u6587\u672c\u6570\u636e\u4ece\u4eba\u7c7b\u53ef\u8bfb\u7684\u5b57\u7b26\u5e8f\u5217\u8f6c\u6362\u4e3a\u673a\u5668\u53ef\u7406\u89e3\u7684\u6570\u503c\u5f62\u5f0f\u3002\u8fd9\u4e2a\u8fc7\u7a0b\u88ab\u79f0\u4e3a\u6587\u672c\u8868\u793a\uff08Text Representation\uff09\u6216\u7279\u5f81\u5de5\u7a0b\uff08Feature Engineering\uff09\u3002\u7531\u4e8e\u673a\u5668\u5b66\u4e60\u7b97\u6cd5\u548c\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u53ea\u80fd\u5904\u7406\u6570\u503c\u578b\u6570\u636e\uff0c\u56e0\u6b64\u6587\u672c\u8868\u793a\u7684\u8d28\u91cf\u5bf9NLP\u4efb\u52a1\u7684\u6027\u80fd\u81f3\u5173\u91cd\u8981\u3002\u4e00\u4e2a\u597d\u7684\u6587\u672c\u8868\u793a\u65b9\u6cd5\u5e94\u8be5\u80fd\u6355\u6349\u6587\u672c\u7684\u8bed\u4e49\u4fe1\u606f\uff0c\u80fd\u6709\u6548\u5730\u7528\u4e8e\u4e0b\u6e38\u4efb\u52a1\u3002\u5e38\u89c1\u7684\u6587\u672c\u8868\u793a\u65b9\u6cd5\u53ef\u4ee5\u5206\u4e3a\u4ee5\u4e0b\u51e0\u7c7b\uff1a<\/p>\n<\/p><\/div>\n

            \n
          • \u57fa\u4e8e\u8bcd\u9891\u7684\u8868\u793a\uff08Frequency-Based Methods\uff09<\/strong>\uff1a\n
              \n
            • \u8bcd\u888b\u6a21\u578b\uff08Bag of Words, BoW\uff09<\/strong>\uff1a\u5c06\u6587\u672c\u8868\u793a\u4e3a\u4e00\u4e2a\u8bcd\u6c47\u8868\u4e2d\u6240\u6709\u8bcd\u7684\u51fa\u73b0\u9891\u7387\u5411\u91cf\u3002\u5b83\u5ffd\u7565\u4e86\u8bcd\u5e8f\u548c\u8bed\u6cd5\u4fe1\u606f\uff0c\u53ea\u5173\u6ce8\u8bcd\u7684\u51fa\u73b0\u4e0e\u5426\u6216\u9891\u7387 \u3002\u4f8b\u5982\uff0c\u53e5\u5b50 \u201cI love NLP and I love AI\u201d \u5728\u8bcd\u6c47\u8868 [\u201cI\u201d, \u201clove\u201d, \u201cNLP\u201d, \u201cand\u201d, \u201cAI\u201d] \u4e0b\u7684BoW\u8868\u793a\u53ef\u80fd\u662f [2, 2, 1, 1, 1]\u3002<\/li>\n
            • TF-IDF\uff08Term Frequency-Inverse Document Frequency\uff09<\/strong>\uff1aTF-IDF\u662f\u4e00\u79cd\u7edf\u8ba1\u65b9\u6cd5\uff0c\u7528\u4e8e\u8bc4\u4f30\u4e00\u4e2a\u8bcd\u5bf9\u4e8e\u4e00\u4e2a\u6587\u4ef6\u96c6\u6216\u4e00\u4e2a\u8bed\u6599\u5e93\u4e2d\u7684\u5176\u4e2d\u4e00\u4efd\u6587\u4ef6\u7684\u91cd\u8981\u7a0b\u5ea6 \u3002\u4e00\u4e2a\u8bcd\u5728\u4e00\u4e2a\u6587\u4ef6\u4e2d\u51fa\u73b0\u7684\u6b21\u6570\u8d8a\u591a\uff08TF\u8d8a\u9ad8\uff09\uff0c\u540c\u65f6\u5728\u6574\u4e2a\u8bed\u6599\u5e93\u4e2d\u51fa\u73b0\u7684\u6587\u4ef6\u6570\u8d8a\u5c11\uff08IDF\u8d8a\u9ad8\uff09\uff0c\u5219\u8fd9\u4e2a\u8bcd\u7684TF-IDF\u503c\u8d8a\u5927\uff0c\u8ba4\u4e3a\u5b83\u8d8a\u80fd\u4ee3\u8868\u8be5\u6587\u4ef6\u7684\u7279\u5f81\u3002<\/li>\n<\/ul>\n<\/li>\n
            • \u57fa\u4e8e\u8bcd\u5411\u91cf\u7684\u8868\u793a\uff08Word Embedding \/ Word Vector\uff09<\/strong>\uff1a\n
                \n
              • One-Hot Encoding<\/strong>\uff1a\u5c06\u6bcf\u4e2a\u8bcd\u8868\u793a\u4e3a\u4e00\u4e2a\u5f88\u957f\u7684\u5411\u91cf\uff0c\u5411\u91cf\u7684\u7ef4\u5ea6\u7b49\u4e8e\u8bcd\u6c47\u8868\u7684\u5927\u5c0f\uff0c\u8be5\u8bcd\u5728\u8bcd\u6c47\u8868\u4e2d\u7684\u7d22\u5f15\u4f4d\u7f6e\u4e3a1\uff0c\u5176\u4f59\u4f4d\u7f6e\u4e3a0 \u3002\u8fd9\u79cd\u65b9\u6cd5\u7b80\u5355\u76f4\u89c2\uff0c\u4f46\u7ef4\u5ea6\u9ad8\u4e14\u7a00\u758f\uff0c\u65e0\u6cd5\u8868\u793a\u8bcd\u4e0e\u8bcd\u4e4b\u95f4\u7684\u8bed\u4e49\u5173\u7cfb\u3002<\/li>\n
              • \u8bcd\u5d4c\u5165\uff08Word Embedding\uff09<\/strong>\uff1a\u5c06\u8bcd\u8bed\u6620\u5c04\u5230\u4e00\u4e2a\u4f4e\u7ef4\u3001\u7a20\u5bc6\u7684\u5b9e\u6570\u5411\u91cf\u7a7a\u95f4\u4e2d\uff0c\u4f7f\u5f97\u8bed\u4e49\u76f8\u8fd1\u7684\u8bcd\u5728\u5411\u91cf\u7a7a\u95f4\u4e2d\u7684\u8ddd\u79bb\u4e5f\u66f4\u8fd1 \u3002Word2Vec \u3001GloVe \u548c FastText \u662f\u5e38\u7528\u7684\u8bcd\u5d4c\u5165\u6a21\u578b\u3002\u8fd9\u4e9b\u6a21\u578b\u901a\u8fc7\u5728\u5927\u89c4\u6a21\u8bed\u6599\u5e93\u4e0a\u8bad\u7ec3\uff0c\u5b66\u4e60\u5230\u8bcd\u8bed\u7684\u5206\u5e03\u5f0f\u8868\u793a\uff0c\u80fd\u591f\u6355\u6349\u5230\u8bcd\u8bed\u4e4b\u95f4\u7684\u8bed\u4e49\u548c\u8bed\u6cd5\u5173\u7cfb\u3002\u4f8b\u5982\uff0c\u901a\u8fc7\u8bcd\u5d4c\u5165\uff0c\u53ef\u4ee5\u53d1\u73b0 \u201cking\u201d \u2013 \u201cman\u201d + \u201cwoman\u201d \u2248 \u201cqueen\u201d \u8fd9\u6837\u7684\u8bed\u4e49\u5173\u7cfb\u3002<\/li>\n<\/ul>\n<\/li>\n
              • \u57fa\u4e8e\u4e0a\u4e0b\u6587\u7684\u8868\u793a\uff08Contextualized Word Representations\uff09<\/strong>\uff1a\n
                  \n
                • ELMo\uff08Embeddings from Language Models\uff09<\/strong>\uff1aELMo\u5229\u7528\u53cc\u5411LSTM\u6a21\u578b\u6765\u751f\u6210\u8bcd\u8bed\u7684\u8868\u793a\uff0c\u80fd\u591f\u6839\u636e\u8bcd\u8bed\u6240\u5904\u7684\u4e0a\u4e0b\u6587\u52a8\u6001\u5730\u8c03\u6574\u5176\u8bcd\u5411\u91cf\uff0c\u4ece\u800c\u89e3\u51b3\u4e00\u8bcd\u591a\u4e49\u7684\u95ee\u9898 \u3002<\/li>\n
                • BERT\uff08Bidirectional Encoder Representations from Transformers\uff09<\/strong>\uff1aBERT\u57fa\u4e8eTransformer\u67b6\u6784\uff0c\u901a\u8fc7\u5728\u5927\u89c4\u6a21\u65e0\u6807\u6ce8\u6587\u672c\u4e0a\u8fdb\u884c\u9884\u8bad\u7ec3\uff0c\u5b66\u4e60\u5230\u6df1\u5ea6\u7684\u53cc\u5411\u4e0a\u4e0b\u6587\u76f8\u5173\u7684\u8bcd\u8868\u793a \u3002BERT\u751f\u6210\u7684\u8bcd\u5411\u91cf\u80fd\u591f\u66f4\u597d\u5730\u6355\u6349\u8bcd\u8bed\u5728\u7279\u5b9a\u4e0a\u4e0b\u6587\u4e2d\u7684\u542b\u4e49\u3002<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n

                  \u9009\u62e9\u5408\u9002\u7684\u6587\u672c\u8868\u793a\u65b9\u6cd5\u53d6\u51b3\u4e8e\u5177\u4f53\u7684NLP\u4efb\u52a1\u3001\u6570\u636e\u91cf\u4ee5\u53ca\u53ef\u7528\u7684\u8ba1\u7b97\u8d44\u6e90\u3002<\/p>\n

                  \n

                  \u8bed\u8a00\u6a21\u578b\uff1a\u9884\u6d4b\u548c\u751f\u6210\u6587\u672c<\/strong><\/h4>\n

                  \u8bed\u8a00\u6a21\u578b\uff08Language Model, LM\uff09\u662f\u81ea\u7136\u8bed\u8a00\u5904\u7406\u4e2d\u7684\u4e00\u4e2a\u6838\u5fc3\u6982\u5ff5\uff0c\u8ba1\u7b97\u4e00\u4e2a\u53e5\u5b50\u6216\u8bcd\u5e8f\u5217\u5728\u67d0\u79cd\u8bed\u8a00\u4e2d\u51fa\u73b0\u7684\u6982\u7387\uff0c\u6216\u8005\u6839\u636e\u5df2\u6709\u7684\u4e0a\u6587\u9884\u6d4b\u4e0b\u4e00\u4e2a\u8bcd\u662f\u4ec0\u4e48\u3002\u8bed\u8a00\u6a21\u578b\u662f\u8bb8\u591aNLP\u4efb\u52a1\u7684\u57fa\u7840\uff0c\u5982\u673a\u5668\u7ffb\u8bd1\u3001\u8bed\u97f3\u8bc6\u522b\u3001\u6587\u672c\u751f\u6210\u3001\u62fc\u5199\u7ea0\u9519\u3001\u8f93\u5165\u6cd5\u9884\u6d4b\u7b49\u3002\u4e00\u4e2a\u597d\u7684\u8bed\u8a00\u6a21\u578b\u5e94\u8be5\u80fd\u51c6\u786e\u5730\u6355\u6349\u8bed\u8a00\u7684\u89c4\u5f8b\uff0c\u5305\u62ec\u8bcd\u6c47\u7684\u642d\u914d\u3001\u53e5\u6cd5\u7ed3\u6784\u4ee5\u53ca\u8bed\u4e49\u8fde\u8d2f\u6027\u3002<\/p>\n<\/p><\/div>\n

                  \n

                  NLP\u7684\u5173\u952e\u6280\u672f\uff1a\u5b9e\u73b0\u8bed\u8a00\u7406\u89e3\u4e0e\u751f\u6210<\/h2>\n

                  \u5206\u8bcd\uff08Tokenization\uff09<\/strong><\/h4>\n

                  \u5206\u8bcd\uff08Tokenization\uff09\uff0c\u4e5f\u79f0\u4e3a\u8bcd\u8bed\u5207\u5206\u6216\u8bcd\u5143\u5316\uff0c\u662fNLP\u4e2d\u6700\u57fa\u7840\u4e14\u91cd\u8981\u7684\u4e00\u6b65\uff0c\u5728\u5904\u7406\u50cf\u4e2d\u6587\u3001\u65e5\u6587\u3001\u6cf0\u6587\u7b49\u6ca1\u6709\u660e\u663e\u8bcd\u95f4\u5206\u9694\u7b26\u7684\u8bed\u8a00\u65f6\u3002\u76ee\u6807\u662f\u5c06\u8fde\u7eed\u7684\u5b57\u7b26\u5e8f\u5217\uff08\u5982\u53e5\u5b50\u6216\u6bb5\u843d\uff09\u5207\u5206\u6210\u4e00\u7cfb\u5217\u6709\u610f\u4e49\u7684\u3001\u72ec\u7acb\u7684\u8bcd\u8bed\u6216\u6807\u8bb0\uff08tokens\uff09\u3002\u5bf9\u4e8e\u82f1\u6587\u7b49\u4ee5\u7a7a\u683c\u5206\u9694\u5355\u8bcd\u7684\u8bed\u8a00\uff0c\u5206\u8bcd\u76f8\u5bf9\u7b80\u5355\uff0c\u4ee5\u7a7a\u683c\u548c\u6807\u70b9\u7b26\u53f7\u4e3a\u754c\u3002<\/p>\n

                  \u5bf9\u4e8e\u4e2d\u6587\uff0c\u5206\u8bcd\u7684\u6311\u6218\u66f4\u5927\uff0c\u56e0\u4e3a\u8bcd\u8bed\u4e4b\u95f4\u6ca1\u6709\u56fa\u5b9a\u7684\u5206\u9694\u7b26\uff0c\u4e14\u5b58\u5728\u5927\u91cf\u7684\u6b67\u4e49\u5207\u5206\u95ee\u9898\u3002<\/p>\n

                  \n

                  \u4f8b\u5982\uff0c\u201c\u7ed3\u5a5a\u7684\u548c\u5c1a\u672a\u7ed3\u5a5a\u7684\u201d\u53ef\u4ee5\u5207\u5206\u4e3a\u201c\u7ed3\u5a5a\/\u7684\/\u548c\/\u5c1a\u672a\/\u7ed3\u5a5a\/\u7684\u201d\u6216\u201c\u7ed3\u5a5a\/\u7684\/\u548c\u5c1a\/\u672a\/\u7ed3\u5a5a\/\u7684\u201d\uff0c\u4e24\u79cd\u5207\u5206\u5728\u8bed\u6cd5\u548c\u8bed\u4e49\u4e0a\u90fd\u53ef\u80fd\u6210\u7acb\uff0c\u9700\u8981\u6839\u636e\u4e0a\u4e0b\u6587\u6765\u5224\u65ad\u3002<\/p>\n<\/blockquote>\n

                  \u5e38\u7528\u7684\u5206\u8bcd\u65b9\u6cd5\u5305\u62ec\u57fa\u4e8e\u8bcd\u5178\u7684\u5339\u914d\u65b9\u6cd5\uff08\u5982\u6700\u5927\u5339\u914d\u6cd5\u3001\u6700\u5c0f\u5339\u914d\u6cd5\uff09\u3001\u57fa\u4e8e\u7edf\u8ba1\u7684\u65b9\u6cd5\uff08\u5982\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578bHMM\u3001\u6761\u4ef6\u968f\u673a\u573aCRF\uff09\u4ee5\u53ca\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u65b9\u6cd5\uff08\u5982BiLSTM-CRF\u3001Transformer\uff09\u3002\u51c6\u786e\u7684\u5206\u8bcd\u662f\u540e\u7eed\u8bcd\u6027\u6807\u6ce8\u3001\u53e5\u6cd5\u5206\u6790\u3001\u8bed\u4e49\u7406\u89e3\u7b49\u4efb\u52a1\u7684\u57fa\u7840\uff0c\u8d28\u91cf\u76f4\u63a5\u5f71\u54cd\u540e\u7eedNLP\u4efb\u52a1\u7684\u6027\u80fd\u3002<\/p>\n

                  \u8bcd\u6027\u6807\u6ce8\uff08Part-of-Speech Tagging\uff09<\/strong><\/h4>\n

                  \u8bcd\u6027\u6807\u6ce8\uff08Part-of-Speech Tagging, POS Tagging\uff09\u662f\u5728\u5206\u8bcd\u7684\u57fa\u7840\u4e0a\uff0c\u4e3a\u6587\u672c\u4e2d\u7684\u6bcf\u4e2a\u8bcd\u8bed\uff08token\uff09\u8d4b\u4e88\u4e00\u4e2a\u5408\u9002\u7684\u8bcd\u6027\u6807\u8bb0\u7684\u8fc7\u7a0b\uff0c\u5982\u540d\u8bcd\uff08noun\uff09\u3001\u52a8\u8bcd\uff08verb\uff09\u3001\u5f62\u5bb9\u8bcd\uff08adjective\uff09\u3001\u526f\u8bcd\uff08adverb\uff09\u3001\u4ecb\u8bcd\uff08preposition\uff09\u3001\u8fde\u8bcd\uff08conjunction\uff09\u7b49 \u3002<\/p>\n

                  \u4f8b\u5982\uff0c\u77e5\u9053\u4e00\u4e2a\u8bcd\u662f\u540d\u8bcd\u53ef\u4ee5\u5e2e\u52a9\u786e\u5b9a\u5b83\u53ef\u80fd\u662f\u4e00\u4e2a\u53e5\u5b50\u7684\u4e3b\u8bed\u6216\u5bbe\u8bed\uff0c\u77e5\u9053\u4e00\u4e2a\u8bcd\u662f\u52a8\u8bcd\u53ef\u4ee5\u5e2e\u52a9\u786e\u5b9a\u53e5\u5b50\u7684\u8c13\u8bed\u3002\u8bcd\u6027\u6807\u6ce8\u7684\u51c6\u786e\u6027\u5bf9\u4e0b\u6e38\u4efb\u52a1\u6709\u663e\u8457\u5f71\u54cd\u3002<\/p>\n

                  \u5e38\u7528\u7684\u8bcd\u6027\u6807\u6ce8\u65b9\u6cd5\u5305\u62ec\u57fa\u4e8e\u89c4\u5219\u7684\u65b9\u6cd5\uff08\u5229\u7528\u8bed\u8a00\u5b66\u4e13\u5bb6\u7f16\u5199\u7684\u89c4\u5219\u8fdb\u884c\u6807\u6ce8\uff09\u3001\u57fa\u4e8e\u7edf\u8ba1\u7684\u65b9\u6cd5\uff08\u5982\u9690\u9a6c\u5c14\u53ef\u592b\u6a21\u578bHMM\u3001\u6700\u5927\u71b5\u6a21\u578bMaxEnt\u3001\u6761\u4ef6\u968f\u673a\u573aCRF\uff0c\u6a21\u578b\u901a\u8fc7\u5728\u5927\u89c4\u6a21\u6807\u6ce8\u8bed\u6599\u5e93\u4e0a\u8fdb\u884c\u8bad\u7ec3\u6765\u5b66\u4e60\u8bcd\u8bed\u53ca\u5176\u8bcd\u6027\u4e4b\u95f4\u7684\u6982\u7387\u5173\u7cfb\uff09\u4ee5\u53ca\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u65b9\u6cd5\uff08\u5982\u4f7f\u7528\u5faa\u73af\u795e\u7ecf\u7f51\u7edcRNN\u3001\u957f\u77ed\u671f\u8bb0\u5fc6\u7f51\u7edcLSTM\u6216Transformer\u7ed3\u5408CRF\u5c42\u8fdb\u884c\u5e8f\u5217\u6807\u6ce8\uff09\u3002<\/p>\n

                  \n

                  \u4f8b\u5982\uff0c\u5bf9\u4e8e\u53e5\u5b50\u201c\u6211\u7231\u81ea\u7136\u8bed\u8a00\u5904\u7406\u201d\uff0c\u8bcd\u6027\u6807\u6ce8\u7684\u7ed3\u679c\u53ef\u80fd\u662f\u201c\u6211\/\u4ee3\u8bcd \u7231\/\u52a8\u8bcd \u81ea\u7136\u8bed\u8a00\u5904\u7406\/\u540d\u8bcd\u201d\u3002<\/p>\n<\/blockquote><\/div>\n

                  \u547d\u540d\u5b9e\u4f53\u8bc6\u522b\uff08Named Entity Recognition, NER\uff09<\/strong><\/h4>\n

                  \u547d\u540d\u5b9e\u4f53\u8bc6\u522b\uff08Named Entity Recognition, NER\uff09\u662f\u4ece\u975e\u7ed3\u6784\u5316\u7684\u6587\u672c\u4e2d\u8bc6\u522b\u51fa\u5177\u6709\u7279\u5b9a\u610f\u4e49\u7684\u5b9e\u4f53\uff0c\u5c06\u5176\u5206\u7c7b\u5230\u9884\u5b9a\u4e49\u7684\u7c7b\u522b\u4e2d\uff0c\u5982\u4eba\u540d\uff08PER\uff09\u3001\u5730\u540d\uff08LOC\uff09\u3001\u7ec4\u7ec7\u673a\u6784\u540d\uff08ORG\uff09\u3001\u65e5\u671f\uff08DATE\uff09\u3001\u65f6\u95f4\uff08TIME\uff09\u3001\u8d27\u5e01\uff08MONEY\uff09\u3001\u767e\u5206\u6bd4\uff08PERCENT\uff09\u7b49\u3002<\/p>\n

                  \n

                  \u4f8b\u5982\uff0c\u5728\u53e5\u5b50\u201c\u82f9\u679c\u516c\u53f8\u4e8e1976\u5e744\u67081\u65e5\u7531\u53f2\u8482\u592b\u00b7\u4e54\u5e03\u65af\u3001\u53f2\u8482\u592b\u00b7\u6c83\u5179\u5c3c\u4e9a\u514b\u548c\u7f57\u7eb3\u5fb7\u00b7\u97e6\u6069\u521b\u7acb\uff0c\u603b\u90e8\u4f4d\u4e8e\u7f8e\u56fd\u52a0\u5229\u798f\u5c3c\u4e9a\u5dde\u5e93\u6bd4\u8482\u8bfa\u201d\u4e2d\uff0cNER\u7cfb\u7edf\u9700\u8981\u8bc6\u522b\u51fa\u201c\u82f9\u679c\u516c\u53f8\u201d\uff08ORG\uff09\u3001\u201c1976\u5e744\u67081\u65e5\u201d\uff08DATE\uff09\u3001\u201c\u53f2\u8482\u592b\u00b7\u4e54\u5e03\u65af\u201d\uff08PER\uff09\u3001\u201c\u53f2\u8482\u592b\u00b7\u6c83\u5179\u5c3c\u4e9a\u514b\u201d\uff08PER\uff09\u3001\u201c\u7f57\u7eb3\u5fb7\u00b7\u97e6\u6069\u201d\uff08PER\uff09\u3001\u201c\u7f8e\u56fd\u201d\uff08LOC\uff09\u3001\u201c\u52a0\u5229\u798f\u5c3c\u4e9a\u5dde\u201d\uff08LOC\uff09\u3001\u201c\u5e93\u6bd4\u8482\u8bfa\u201d\uff08LOC\uff09\u3002<\/p>\n<\/blockquote>\n

                  NER\u5bf9\u4e8e\u4fe1\u606f\u62bd\u53d6\u3001\u77e5\u8bc6\u56fe\u8c31\u6784\u5efa\u3001\u95ee\u7b54\u7cfb\u7edf\u3001\u673a\u5668\u7ffb\u8bd1\u7b49\u9ad8\u7ea7NLP\u5e94\u7528\u5177\u6709\u91cd\u8981\u610f\u4e49 \u3002\u4f8b\u5982\uff0c\u5728\u673a\u5668\u7ffb\u8bd1\u4e2d\uff0c\u8bc6\u522b\u51fa\u547d\u540d\u5b9e\u4f53\u5e76\u5c06\u5176\u4f5c\u4e3a\u4e00\u4e2a\u6574\u4f53\u8fdb\u884c\u7ffb\u8bd1\uff0c\u53ef\u4ee5\u907f\u514d\u9010\u8bcd\u7ffb\u8bd1\u53ef\u80fd\u5bfc\u81f4\u7684\u9519\u8bef \u3002\u4e3b\u6d41\u7684NER\u65b9\u6cd5\u5305\u62ec\u57fa\u4e8e\u89c4\u5219\u7684\u65b9\u6cd5\u3001\u57fa\u4e8e\u8bcd\u5178\u7684\u65b9\u6cd5\u3001\u57fa\u4e8e\u7edf\u8ba1\u673a\u5668\u5b66\u4e60\u7684\u65b9\u6cd5\uff08\u5982HMM\u3001CRF\u3001\u652f\u6301\u5411\u91cf\u673aSVM\uff09\u4ee5\u53ca\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u65b9\u6cd5\uff08\u5982BiLSTM-CRF\u3001Transformer-CRF\u3001\u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\u5982BERT\u7684\u5fae\u8c03\uff09\u3002\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u7531\u4e8e\u5176\u5f3a\u5927\u7684\u7279\u5f81\u5b66\u4e60\u80fd\u529b\uff0c\u5728NER\u4efb\u52a1\u4e0a\u53d6\u5f97\u4e86\u663e\u8457\u7684\u6210\u679c\u3002<\/p>\n

                  \"\" <\/p>\n

                  \u8bcd\u5d4c\u5165\uff08Word Embedding\uff09\u4e0e\u8bcd\u5411\u91cf<\/strong><\/h4>\n

                  \u8bcd\u5d4c\u5165\uff08Word Embedding\uff09\u662f\u4e00\u79cd\u5c06\u8bcd\u8bed\u4ece\u9ad8\u7ef4\u7a00\u758f\u7684\u72ec\u70ed\u7f16\u7801\u8868\u793a\u6620\u5c04\u5230\u4f4e\u7ef4\u7a20\u5bc6\u7684\u5b9e\u6570\u5411\u91cf\u7a7a\u95f4\u7684\u6280\u672f\uff0c\u4f7f\u5f97\u8bed\u4e49\u76f8\u4f3c\u7684\u8bcd\u8bed\u5728\u5411\u91cf\u7a7a\u95f4\u4e2d\u7684\u8ddd\u79bb\u8f83\u8fd1\u3002\u8fd9\u4e9b\u4f4e\u7ef4\u5411\u91cf\u88ab\u79f0\u4e3a\u8bcd\u5411\u91cf\uff08Word Vectors\uff09<\/strong>\u3002\u8bcd\u5d4c\u5165\u7684\u6838\u5fc3\u601d\u60f3\u662f\u201c\u5206\u5e03\u5047\u8bf4\u201d\uff08Distributional Hypothesis\uff09\uff0c\u5177\u6709\u76f8\u4f3c\u4e0a\u4e0b\u6587\u7684\u8bcd\u8bed\u5f80\u5f80\u5177\u6709\u76f8\u4f3c\u7684\u8bed\u4e49\u3002\u901a\u8fc7\u5728\u5927\u89c4\u6a21\u65e0\u6807\u6ce8\u6587\u672c\u8bed\u6599\u5e93\u4e0a\u8fdb\u884c\u8bad\u7ec3\uff0c\u8bcd\u5d4c\u5165\u6a21\u578b\u80fd\u5b66\u4e60\u5230\u8bcd\u8bed\u7684\u5206\u5e03\u5f0f\u8868\u793a\uff0c\u6355\u6349\u8bcd\u8bed\u4e4b\u95f4\u7684\u8bed\u4e49\u548c\u8bed\u6cd5\u5173\u7cfb\u3002<\/p>\n

                    \n
                  • Word2Vec\uff1a<\/strong>\u662fGoogle\u63a8\u51fa\u7684\u4e00\u79cd\u9ad8\u6548\u7684\u5b66\u4e60\u8bcd\u5411\u91cf\u7684\u5de5\u5177\u548c\u7b97\u6cd5\u96c6\u5408\uff0c\u80fd\u5c06\u8bcd\u8bed\u8f6c\u5316\u4e3a\u56fa\u5b9a\u7ef4\u5ea6\u7684\u7a20\u5bc6\u5411\u91cf\uff08\u5373\u8bcd\u5d4c\u5165\uff09\uff0c\u4f7f\u8bed\u4e49\u76f8\u8fd1\u7684\u8bcd\u8bed\u5728\u5411\u91cf\u7a7a\u95f4\u4e2d\u7684\u4f4d\u7f6e\u4e5f\u76f8\u8fd1 \u3002Word2Vec\u4e3b\u8981\u5305\u542b\u4e24\u79cd\u6a21\u578b\u67b6\u6784\uff1a\u8fde\u7eed\u8bcd\u888b\u6a21\u578b\uff08Continuous Bag-of-Words, CBOW\uff09\u548c\u8df3\u5b57\u6a21\u578b\uff08Skip-Gram\uff09<\/strong>\u3002\u76ee\u6807\u90fd\u662f\u5b66\u4e60\u9ad8\u8d28\u91cf\u7684\u8bcd\u5411\u91cf\uff0c\u4f46\u8bad\u7ec3\u7f51\u7edc\u7684\u65b9\u5f0f\u6709\u6240\u4e0d\u540c\u3002<\/li>\n
                  • GloVe\uff08Global Vectors for Word Representation\uff09\uff1a<\/strong>\u662f\u53e6\u4e00\u79cd\u5e7f\u6cdb\u4f7f\u7528\u7684\u8bcd\u5d4c\u5165\u65b9\u6cd5\uff0c\u7531\u65af\u5766\u798f\u5927\u5b66\u7684\u7814\u7a76\u56e2\u961f\u4e8e2014\u5e74\u63d0\u51fa\u3002GloVe\u7684\u6838\u5fc3\u601d\u60f3\u662f\u5229\u7528\u8bed\u6599\u5e93\u4e2d\u5168\u5c40\u7684\u8bcd\u4e0e\u8bcd\u4e4b\u95f4\u7684\u5171\u73b0\u7edf\u8ba1\u4fe1\u606f\u6765\u5b66\u4e60\u8bcd\u5411\u91cf \u3002<\/li>\n<\/ul>\n

                    \u673a\u5668\u7ffb\u8bd1\uff08Machine Translation\uff09<\/strong><\/h4>\n

                    \u673a\u5668\u7ffb\u8bd1\uff08Machine Translation, MT\uff09\u76ee\u6807\u662f\u5229\u7528\u8ba1\u7b97\u673a\u81ea\u52a8\u5c06\u4e00\u79cd\u81ea\u7136\u8bed\u8a00\uff08\u6e90\u8bed\u8a00\uff09\u7684\u6587\u672c\u6216\u8bed\u97f3\u7ffb\u8bd1\u6210\u53e6\u4e00\u79cd\u81ea\u7136\u8bed\u8a00\uff08\u76ee\u6807\u8bed\u8a00\uff09\u3002<\/p>\n

                    \u673a\u5668\u7ffb\u8bd1\u7684\u53d1\u5c55\u7ecf\u5386\u4e86\u591a\u4e2a\u9636\u6bb5\uff1a<\/p>\n

                      \n
                    • \u57fa\u4e8e\u89c4\u5219\u7684\u673a\u5668\u7ffb\u8bd1<\/strong>\uff08Rule-Based Machine Translation, RBMT\uff09\uff1a\u4e3b\u8981\u4f9d\u8d56\u4e8e\u8bed\u8a00\u5b66\u5bb6\u7f16\u5199\u7684\u53cc\u8bed\u8bcd\u5178\u548c\u8bed\u6cd5\u89c4\u5219\u3002<\/li>\n
                    • \u57fa\u4e8e\u7edf\u8ba1\u7684\u673a\u5668\u7ffb\u8bd1<\/strong>\uff08Statistical Machine Translation, SMT\uff09\uff1a\u5bf9\u5927\u89c4\u6a21\u53cc\u8bed\u5e73\u884c\u8bed\u6599\u5e93\u7684\u7edf\u8ba1\u5206\u6790\uff0c\u901a\u8fc7\u6784\u5efa\u7ffb\u8bd1\u6a21\u578b\u3001\u8bed\u8a00\u6a21\u578b\u7b49\u7ec4\u4ef6\uff0c\u5bfb\u627e\u6982\u7387\u6700\u9ad8\u7684\u7ffb\u8bd1\u7ed3\u679c\u3002<\/li>\n
                    • \u57fa\u4e8e\u795e\u7ecf\u7f51\u7edc\u7684\u673a\u5668\u7ffb\u8bd1<\/strong>\uff08Neural Machine Translation, NMT\uff09\uff1a\u91c7\u7528\u7aef\u5230\u7aef\u7684\u5b66\u4e60\u65b9\u5f0f\uff0c\u4f7f\u7528\u795e\u7ecf\u7f51\u7edc\uff08\u901a\u5e38\u662f\u7f16\u7801\u5668-\u89e3\u7801\u5668\u67b6\u6784\uff0c\u5982Seq2Seq\u6a21\u578b\uff0c\u4ee5\u53ca\u540e\u6765\u7684Transformer\u6a21\u578b\uff09\u76f4\u63a5\u4ece\u6e90\u8bed\u8a00\u5230\u76ee\u6807\u8bed\u8a00\u8fdb\u884c\u7ffb\u8bd1\uff0c\u65e0\u9700\u624b\u5de5\u8bbe\u8ba1\u590d\u6742\u7684\u7279\u5f81 \u3002<\/li>\n<\/ul>\n

                      \u60c5\u611f\u5206\u6790\uff08Sentiment Analysis\uff09<\/strong><\/h4>\n

                      \u60c5\u611f\u5206\u6790\uff08Sentiment Analysis\uff09\uff0c\u53c8\u79f0\u610f\u89c1\u6316\u6398\uff08Opinion Mining\uff09\u6216\u6587\u672c\u503e\u5411\u6027\u8bc6\u522b\uff08Text Orientation Identification\uff09\uff0c\u8bc6\u522b\u548c\u63d0\u53d6\u6587\u672c\u4e2d\u6240\u8868\u8fbe\u7684\u4e3b\u89c2\u4fe1\u606f\uff0c\u5982\u4f5c\u8005\u7684\u60c5\u611f\u3001\u6001\u5ea6\u3001\u8bc4\u4ef7\u3001\u60c5\u7eea\u7b49\u3002\u60c5\u611f\u5206\u6790\u7684\u76ee\u6807\u901a\u5e38\u662f\u5224\u65ad\u6587\u672c\u7684\u60c5\u611f\u6781\u6027\uff08\u5982\u79ef\u6781\u3001\u6d88\u6781\u3001\u4e2d\u6027\uff09\uff0c\u6216\u8005\u8bc6\u522b\u66f4\u7ec6\u81f4\u7684\u60c5\u611f\u7c7b\u522b\uff08\u5982\u559c\u3001\u6012\u3001\u54c0\u3001\u4e50\u3001\u60e7\u7b49\uff09\u3002<\/p>\n

                      \u8bed\u97f3\u8bc6\u522b\uff08Speech Recognition\uff09<\/strong><\/h4>\n

                      \u4e5f\u79f0\u4e3a\u81ea\u52a8\u8bed\u97f3\u8bc6\u522b\uff08Automatic Speech Recognition, ASR\uff09\uff0c\u76ee\u6807\u662f\u5c06\u4eba\u7c7b\u7684\u53e3\u8bed\u8bed\u97f3\u8f6c\u6362\u6210\u76f8\u5e94\u7684\u6587\u672c\u5f62\u5f0f\u3002\u7b80\u5355\u6765\u8bf4\uff0c\u5c31\u662f\u8ba9\u8ba1\u7b97\u673a\u80fd\u201c\u542c\u61c2\u201d\u4eba\u8bf4\u7684\u8bdd\uff0c\u5c06\u5176\u8f6c\u5316\u4e3a\u53ef\u7f16\u8f91\u548c\u5904\u7406\u7684\u6587\u5b57\u3002<\/p>\n

                      \u8bed\u97f3\u5408\u6210\uff08Speech Synthesis\uff09<\/strong><\/h4>\n

                      \u4e5f\u79f0\u4e3a\u6587\u672c\u8f6c\u8bed\u97f3\uff08Text-to-Speech, TTS\uff09\uff0c\u662f\u8bed\u97f3\u8bc6\u522b\u7684\u9006\u8fc7\u7a0b\uff0c\u76ee\u6807\u662f\u5c06\u6587\u672c\u4fe1\u606f\u8f6c\u6362\u6210\u4eba\u7c7b\u53ef\u542c\u7684\u81ea\u7136\u6d41\u7545\u7684\u8bed\u97f3\u8f93\u51fa\u3002\u7b80\u5355\u6765\u8bf4\uff0c\u5c31\u662f\u8ba9\u8ba1\u7b97\u673a\u80fd\u201c\u8bf4\u8bdd\u201d\u3002<\/p>\n

                      NLP\u7684\u4e3b\u6d41\u6a21\u578b\u4e0e\u65b9\u6cd5\uff1a\u4ece\u4f20\u7edf\u5230\u6df1\u5ea6\u5b66\u4e60<\/h2>\n

                      \u4f20\u7edf\u65b9\u6cd5\uff1a\u57fa\u4e8e\u89c4\u5219\u548c\u7edf\u8ba1\u6a21\u578b<\/strong><\/h4>\n

                      \u5728\u6df1\u5ea6\u5b66\u4e60\u5174\u8d77\u4e4b\u524d\uff0cNLP\u4e3b\u8981\u4f9d\u8d56\u4e8e\u57fa\u4e8e\u89c4\u5219\u7684\u65b9\u6cd5\u548c\u7edf\u8ba1\u6a21\u578b\u3002<\/p>\n

                        \n
                      • \u57fa\u4e8e\u89c4\u5219\u7684\u65b9\u6cd5<\/strong>\u5229\u7528\u8bed\u8a00\u5b66\u4e13\u5bb6\u624b\u5de5\u7f16\u5199\u7684\u89c4\u5219\u96c6\u6765\u5904\u7406\u6587\u672c\uff0c\u4f8b\u5982\uff0c\u901a\u8fc7\u5b9a\u4e49\u8bed\u6cd5\u89c4\u5219\u8fdb\u884c\u53e5\u6cd5\u5206\u6790\uff0c\u6216\u8005\u901a\u8fc7\u6784\u5efa\u8bcd\u5178\u548c\u6a21\u5f0f\u5339\u914d\u89c4\u5219\u8fdb\u884c\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u548c\u60c5\u611f\u5206\u6790\u3002\u4f18\u70b9\u5728\u4e8e\u89c4\u5219\u5177\u6709\u8f83\u597d\u7684\u53ef\u89e3\u91ca\u6027\uff0c\u4f46\u5728\u9762\u5bf9\u8bed\u8a00\u7684\u591a\u6837\u6027\u3001\u6b67\u4e49\u6027\u548c\u52a8\u6001\u6027\u65f6\uff0c\u89c4\u5219\u7684\u8986\u76d6\u5ea6\u548c\u7ef4\u62a4\u6210\u672c\u6210\u4e3a\u4e3b\u8981\u74f6\u9888\u3002<\/li>\n
                      • \u7edf\u8ba1\u6a21\u578b<\/strong>\u4ece\u5927\u89c4\u6a21\u6587\u672c\u8bed\u6599\u5e93\u4e2d\u5b66\u4e60\u8bed\u8a00\u7684\u7edf\u8ba1\u89c4\u5f8b\u3002\u4f8b\u5982\uff0cN-gram\u8bed\u8a00\u6a21\u578b\u901a\u8fc7\u7edf\u8ba1\u8bcd\u5e8f\u5217\u51fa\u73b0\u7684\u9891\u7387\u6765\u9884\u6d4b\u4e0b\u4e00\u4e2a\u8bcd\u6216\u8bc4\u4f30\u53e5\u5b50\u7684\u6982\u7387\u3002<\/li>\n<\/ul>\n

                        \"\" <\/p>\n

                        \u6df1\u5ea6\u5b66\u4e60\u65b9\u6cd5\uff1a\u795e\u7ecf\u7f51\u7edc\u7684\u5d1b\u8d77<\/strong><\/h4>\n

                        \u968f\u7740\u8ba1\u7b97\u80fd\u529b\u7684\u63d0\u5347\u548c\u5927\u89c4\u6a21\u6807\u6ce8\u6570\u636e\u7684\u53ef\u7528\u6027\uff0c\u6df1\u5ea6\u5b66\u4e60\u6280\u672f\uff0c\u7279\u522b\u662f\u795e\u7ecf\u7f51\u7edc\u6a21\u578b\uff0c\u5728NLP\u9886\u57df\u53d6\u5f97\u4e86\u7a81\u7834\u6027\u8fdb\u5c55\uff0c\u9010\u6e10\u6210\u4e3a\u4e3b\u6d41\u65b9\u6cd5\u3002\u4e0e\u4f20\u7edf\u65b9\u6cd5\u76f8\u6bd4\uff0c\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\u80fd\u81ea\u52a8\u4ece\u539f\u59cb\u6570\u636e\u4e2d\u5b66\u4e60\u5c42\u6b21\u5316\u7684\u7279\u5f81\u8868\u793a\uff0c\u907f\u514d\u4e86\u7e41\u7410\u7684\u7279\u5f81\u5de5\u7a0b\uff0c\u80fd\u66f4\u597d\u5730\u6355\u6349\u6587\u672c\u4e2d\u7684\u590d\u6742\u6a21\u5f0f\u548c\u957f\u8ddd\u79bb\u4f9d\u8d56\u5173\u7cfb\u3002<\/p>\n

                        \u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\uff1aBERT\u4e0eGPT\u7cfb\u5217<\/strong><\/h4>\n

                        \u9884\u8bad\u7ec3\u8bed\u8a00\u6a21\u578b\uff08Pre-trained Language Models, PLMs\uff09\u662f\u8fd1\u5e74\u6765NLP\u9886\u57df\u6700\u91cd\u8981\u7684\u8fdb\u5c55\u4e4b\u4e00\uff0c\u6838\u5fc3\u601d\u60f3\u662f\u5148\u5728\u8d85\u5927\u89c4\u6a21\u7684\u65e0\u6807\u6ce8\u6587\u672c\u8bed\u6599\u5e93\u4e0a\u8fdb\u884c\u9884\u8bad\u7ec3\uff0c\u5b66\u4e60\u901a\u7528\u7684\u8bed\u8a00\u8868\u793a\uff0c\u7136\u540e\u9488\u5bf9\u7279\u5b9a\u7684\u4e0b\u6e38\u4efb\u52a1\u8fdb\u884c\u5fae\u8c03\uff08Fine-tuning\uff09\u3002\u8fd9\u79cd\u201c\u9884\u8bad\u7ec3+\u5fae\u8c03\u201d\u7684\u8303\u5f0f\u6781\u5927\u5730\u63d0\u5347\u4e86NLP\u6a21\u578b\u7684\u6cdb\u5316\u80fd\u529b\u548c\u6027\u80fd\uff0c\u51cf\u5c11\u4e86\u5bf9\u5927\u91cf\u6807\u6ce8\u6570\u636e\u7684\u4f9d\u8d56\u3002<\/p>\n

                        \u4e0b\u8868\u603b\u7ed3\u4e86BERT\u548cGPT\u7cfb\u5217\u6a21\u578b\u7684\u4e3b\u8981\u7279\u70b9\uff1a<\/p>\n

                        \n\n\n\n\n\n\n\n\n\n
                        \u7279\u6027<\/th>\nBERT (\u53ca\u7c7b\u4f3c\u6a21\u578b\u5982 RoBERTa, ALBERT)<\/th>\nGPT \u7cfb\u5217 (GPT-1\/2\/3, ChatGPT, GPT-4)<\/th>\n<\/tr>\n<\/thead>\n
                        \u67b6\u6784\u57fa\u7840<\/strong><\/td>\nTransformer \u7f16\u7801\u5668<\/td>\nTransformer \u89e3\u7801\u5668<\/td>\n<\/tr>\n
                        \u9884\u8bad\u7ec3\u4efb\u52a1<\/strong><\/td>\n\u63a9\u7801\u8bed\u8a00\u6a21\u578b (MLM), \u4e0b\u4e00\u53e5\u9884\u6d4b (NSP)<\/td>\n\u81ea\u56de\u5f52\u8bed\u8a00\u6a21\u578b (\u4ece\u5de6\u5230\u53f3\u9884\u6d4b)<\/td>\n<\/tr>\n
                        \u4e0a\u4e0b\u6587\u7406\u89e3<\/strong><\/td>\n\u53cc\u5411 (\u540c\u65f6\u8003\u8651\u5de6\u53f3\u4e0a\u4e0b\u6587)<\/td>\n\u5355\u5411 (\u4ec5\u8003\u8651\u5de6\u4fa7\/\u4e0a\u6587)<\/td>\n<\/tr>\n
                        \u4e3b\u8981\u4f18\u52bf<\/strong><\/td>\n\u6587\u672c\u7406\u89e3\u3001\u5206\u7c7b\u3001\u4fe1\u606f\u62bd\u53d6<\/td>\n\u6587\u672c\u751f\u6210\u3001\u5bf9\u8bdd\u3001\u521b\u9020\u6027\u5199\u4f5c<\/td>\n<\/tr>\n
                        \u5178\u578b\u5e94\u7528<\/strong><\/td>\n\u6587\u672c\u5206\u7c7b\u3001\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u3001\u95ee\u7b54<\/td>\n\u6587\u672c\u751f\u6210\u3001\u804a\u5929\u673a\u5668\u4eba\u3001\u4ee3\u7801\u751f\u6210\u3001\u6458\u8981<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

                        \"\" <\/p>\n

                        \u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08LLMs\uff09\u7684\u7a81\u7834<\/strong><\/h4>\n

                        LLMs\u7684\u7a81\u7834\u6027\u8fdb\u5c55\u4e3b\u8981\u4f53\u73b0\u5728\u4ee5\u4e0b\u51e0\u4e2a\u65b9\u9762\uff1a<\/p>\n<\/p><\/div>\n

                          \n
                        • \u96f6\u6837\u672c\uff08Zero-shot\uff09\u548c\u5c0f\u6837\u672c\uff08Few-shot\uff09\u5b66\u4e60\u80fd\u529b<\/strong>\uff1aLLMs\u80fd\u5728\u6ca1\u6709\u6216\u4ec5\u6709\u5c11\u91cf\u7279\u5b9a\u4efb\u52a1\u6807\u6ce8\u6570\u636e\u7684\u60c5\u51b5\u4e0b\uff0c\u901a\u8fc7\u81ea\u7136\u8bed\u8a00\u6307\u4ee4\uff08Prompt\uff09\u5b8c\u6210\u5404\u79cd\u590d\u6742\u7684NLP\u4efb\u52a1\uff0c\u5c55\u73b0\u51fa\u5f3a\u5927\u7684\u6cdb\u5316\u80fd\u529b\u548c\u5feb\u901f\u9002\u5e94\u65b0\u4efb\u52a1\u7684\u80fd\u529b\u3002<\/li>\n
                        • \u6d8c\u73b0\u80fd\u529b\uff08Emergent Abilities\uff09<\/strong>\uff1a\u968f\u7740\u6a21\u578b\u89c4\u6a21\u7684\u589e\u5927\uff0cLLMs\u5728\u67d0\u4e9b\u4efb\u52a1\u4e0a\u7684\u6027\u80fd\u4f1a\u7a81\u7136\u51fa\u73b0\u663e\u8457\u63d0\u5347\uff0c\u8868\u73b0\u51fa\u4e00\u4e9b\u5728\u8f83\u5c0f\u6a21\u578b\u4e2d\u6ca1\u6709\u89c2\u5bdf\u5230\u7684\u65b0\u80fd\u529b\uff0c\u4f8b\u5982\u590d\u6742\u7684\u63a8\u7406\u3001\u591a\u6b65\u95ee\u9898\u89e3\u51b3\u7b49\u3002<\/li>\n
                        • \u66f4\u5f3a\u7684\u4e0a\u4e0b\u6587\u5b66\u4e60\u548c\u6307\u4ee4\u9075\u5faa\u80fd\u529b<\/strong>\uff1aLLMs\u80fd\u66f4\u597d\u5730\u7406\u89e3\u590d\u6742\u7684\u6307\u4ee4\uff0c\u6839\u636e\u4e0a\u4e0b\u6587\u751f\u6210\u66f4\u76f8\u5173\u3001\u66f4\u4e00\u81f4\u7684\u56de\u590d\u3002<\/li>\n
                        • \u591a\u6a21\u6001\u80fd\u529b<\/strong>\uff1a\u4e00\u4e9b\u5148\u8fdb\u7684LLMs\uff08\u5982GPT-4\uff09\u5f00\u59cb\u5177\u5907\u5904\u7406\u548c\u7406\u89e3\u591a\u79cd\u6a21\u6001\u4fe1\u606f\uff08\u5982\u6587\u672c\u3001\u56fe\u50cf\uff09\u7684\u80fd\u529b\uff0c\u8fdb\u4e00\u6b65\u62d3\u5c55\u4e86\u5176\u5e94\u7528\u573a\u666f\u3002<\/li>\n<\/ul>\n

                          NLP\u9762\u4e34\u7684\u4e3b\u8981\u6311\u6218\uff1a\u4e3a\u4f55\u7406\u89e3\u8bed\u8a00\u5982\u6b64\u56f0\u96be\uff1f<\/h2>\n

                          \u8bed\u8a00\u7684\u6b67\u4e49\u6027<\/strong><\/h4>\n

                          \u540c\u4e00\u4e2a\u8bcd\u3001\u77ed\u8bed\u6216\u53e5\u5b50\u5728\u4e0d\u540c\u7684\u4e0a\u4e0b\u6587\u4e2d\u53ef\u80fd\u5177\u6709\u591a\u79cd\u4e0d\u540c\u7684\u542b\u4e49\u3002\u4f8b\u5982\uff1a<\/p>\n

                            \n
                          • \u8bcd\u6cd5\u6b67\u4e49<\/strong>\uff1a\u4e00\u4e2a\u8bcd\u53ef\u80fd\u6709\u591a\u4e2a\u8bcd\u6027\uff08\u5982\u201c\u6253\u201d\u53ef\u4ee5\u662f\u52a8\u8bcd\uff0c\u4e5f\u53ef\u4ee5\u662f\u91cf\u8bcd\uff09\u6216\u591a\u4e2a\u8bcd\u4e49\uff08\u5982\u201cbank\u201d\u53ef\u4ee5\u6307\u94f6\u884c\uff0c\u4e5f\u53ef\u4ee5\u6307\u6cb3\u5cb8\uff09\u3002<\/li>\n
                          • \u53e5\u6cd5\u6b67\u4e49<\/strong>\uff1a\u4e00\u4e2a\u53e5\u5b50\u53ef\u80fd\u6709\u591a\u79cd\u5408\u6cd5\u7684\u53e5\u6cd5\u7ed3\u6784\uff0c\u5bfc\u81f4\u4e0d\u540c\u7684\u89e3\u91ca\u3002\u4f8b\u5982\uff0c\u201cFlying planes can be dangerous\u201d\u53ef\u4ee5\u7406\u89e3\u4e3a\u201c\u9a7e\u9a76\u98de\u673a\u53ef\u80fd\u662f\u5371\u9669\u7684\u201d\u6216\u201c\u6b63\u5728\u98de\u7684\u98de\u673a\u53ef\u80fd\u662f\u5371\u9669\u7684\u201d\u3002<\/li>\n
                          • \u8bed\u4e49\u6b67\u4e49<\/strong>\uff1a\u5373\u4f7f\u53e5\u6cd5\u7ed3\u6784\u6e05\u6670\uff0c\u53e5\u5b50\u7684\u8bed\u4e49\u4e5f\u53ef\u80fd\u5b58\u5728\u6b67\u4e49\uff0c\u5c24\u5176\u662f\u5728\u6d89\u53ca\u4ee3\u8bcd\u6307\u4ee3\u3001\u7701\u7565\u6216\u9690\u55bb\u65f6\u3002<\/li>\n
                          • \u8bed\u7528\u6b67\u4e49<\/strong>\uff1a\u8bf4\u8bdd\u8005\u7684\u771f\u5b9e\u610f\u56fe\u53ef\u80fd\u4e0e\u5176\u5b57\u9762\u610f\u601d\u4e0d\u540c\uff0c\u4f8b\u5982\u8bbd\u523a\u3001\u53cd\u8bed\u7b49\u3002<\/li>\n<\/ul>\n

                            \u6d88\u9664\u8fd9\u4e9b\u6b67\u4e49\u9700\u8981\u6a21\u578b\u5177\u5907\u5f3a\u5927\u7684\u4e0a\u4e0b\u6587\u7406\u89e3\u80fd\u529b\u548c\u4e30\u5bcc\u7684\u4e16\u754c\u77e5\u8bc6\uff0c\u5bf9\u4e8e\u5f53\u524d\u7684NLP\u7cfb\u7edf\u6765\u8bf4\u4ecd\u7136\u662f\u4e00\u4e2a\u96be\u9898\u3002<\/p>\n

                            \n

                            \u4e0a\u4e0b\u6587\u7406\u89e3\u7684\u590d\u6742\u6027<\/strong><\/h4>\n

                            \u51c6\u786e\u7406\u89e3\u8bed\u8a00\u7684\u542b\u4e49\u9ad8\u5ea6\u4f9d\u8d56\u4e8e\u4e0a\u4e0b\u6587\u4fe1\u606f\uff0c\u5305\u62ec\u5bf9\u8bdd\u7684\u5148\u524d\u5185\u5bb9\u3001\u8bf4\u8bdd\u8005\u548c\u542c\u8bdd\u8005\u7684\u80cc\u666f\u77e5\u8bc6\u3001\u5bf9\u8bdd\u53d1\u751f\u7684\u573a\u666f\u4ee5\u53ca\u5171\u4eab\u7684\u793e\u4f1a\u6587\u5316\u5e38\u8bc6\u7b49\u3002NLP\u6a21\u578b\u9700\u8981\u80fd\u6355\u6349\u6709\u6548\u5229\u7528\u8fd9\u4e9b\u590d\u6742\u7684\u4e0a\u4e0b\u6587\u4fe1\u606f\u3002\u4f8b\u5982\uff0c\u4ee3\u8bcd\uff08\u5982\u201c\u4ed6\u201d\u3001\u201c\u5b83\u201d\uff09\u7684\u5177\u4f53\u6307\u4ee3\u5bf9\u8c61\u9700\u8981\u6839\u636e\u4e0a\u4e0b\u6587\u6765\u786e\u5b9a\u3002\u4e00\u4e2a\u8bcd\u5728\u7279\u5b9a\u9886\u57df\u6216\u6587\u5316\u80cc\u666f\u4e0b\u7684\u542b\u4e49\u53ef\u80fd\u4e0e\u901a\u7528\u542b\u4e49\u6709\u6240\u4e0d\u540c\u3002<\/p>\n

                            \u6570\u636e\u7a00\u758f\u4e0e\u6807\u6ce8\u96be\u9898<\/strong><\/h4>\n

                            \u8bb8\u591aNLP\u4efb\u52a1\uff0c\u7279\u522b\u662f\u76d1\u7763\u5b66\u4e60\u4efb\u52a1\uff0c\u4e25\u91cd\u4f9d\u8d56\u4e8e\u5927\u89c4\u6a21\u9ad8\u8d28\u91cf\u7684\u6807\u6ce8\u6570\u636e\u3002\u83b7\u53d6\u8fd9\u6837\u7684\u6807\u6ce8\u6570\u636e\u6210\u672c\u9ad8\u6602\u3001\u8017\u65f6\u8017\u529b\uff0c\u5c24\u5176\u5728\u7279\u5b9a\u9886\u57df\u6216\u5c0f\u4f17\u8bed\u8a00\u4e2d\u3002\u6570\u636e\u7a00\u758f\u95ee\u9898\uff0c\u8bb8\u591a\u5408\u7406\u7684\u8bed\u8a00\u8868\u8fbe\u5728\u8bad\u7ec3\u6570\u636e\u4e2d\u51fa\u73b0\u7684\u9891\u7387\u6781\u4f4e\u751a\u81f3\u6ca1\u6709\u51fa\u73b0\u8fc7\uff0c\u4f1a\u5bfc\u81f4\u6a21\u578b\u96be\u4ee5\u5b66\u4e60\u5230\u8fd9\u4e9b\u8868\u8fbe\u7684\u89c4\u5f8b\u3002<\/p>\n

                            \u6807\u6ce8\u8fc7\u7a0b\u672c\u8eab\u4e5f\u53ef\u80fd\u5f15\u5165\u4e3b\u89c2\u6027\u548c\u4e0d\u4e00\u81f4\u6027\u3002\u5982\u4f55\u6709\u6548\u5730\u5229\u7528\u5c11\u91cf\u6807\u6ce8\u6570\u636e\uff08\u5c0f\u6837\u672c\u5b66\u4e60\uff09\u6216\u5b8c\u5168\u65e0\u6807\u6ce8\u6570\u636e\u8fdb\u884c\u5b66\u4e60\uff0c\u4ecd\u7136\u662fNLP\u9886\u57df\u7684\u91cd\u8981\u7814\u7a76\u65b9\u5411\u3002<\/p>\n

                            \u9886\u57df\u77e5\u8bc6\u7684\u878d\u5408<\/strong><\/h4>\n

                            \u81ea\u7136\u8bed\u8a00\u4e2d\u8574\u542b\u7740\u5927\u91cf\u7684\u9886\u57df\u7279\u5b9a\u77e5\u8bc6\u548c\u5e38\u8bc6\u3002\u4f8b\u5982\uff0c\u5728\u533b\u7597\u9886\u57df\u7684\u6587\u672c\u4e2d\uff0c\u7406\u89e3\u75be\u75c5\u3001\u75c7\u72b6\u3001\u836f\u7269\u53ca\u5176\u76f8\u4e92\u5173\u7cfb\u81f3\u5173\u91cd\u8981\uff1b\u5728\u6cd5\u5f8b\u6587\u4e66\u4e2d\uff0c\u7406\u89e3\u6cd5\u5f8b\u6761\u6b3e\u3001\u6848\u4f8b\u548c\u7a0b\u5e8f\u662f\u5fc5\u8981\u7684\u3002NLP\u6a21\u578b\u9700\u8981\u80fd\u6709\u6548\u5730\u878d\u5408\u8fd9\u4e9b\u9886\u57df\u77e5\u8bc6\u624d\u80fd\u8fdb\u884c\u51c6\u786e\u7684\u89e3\u8bfb\u548c\u63a8\u7406\u3002\u5c06\u7ed3\u6784\u5316\u7684\u77e5\u8bc6\u5e93\uff08\u5982\u77e5\u8bc6\u56fe\u8c31\uff09\u4e0e\u975e\u7ed3\u6784\u5316\u7684\u6587\u672c\u4fe1\u606f\u6709\u6548\u5730\u7ed3\u5408\u8d77\u6765\uff0c\u8ba9\u6a21\u578b\u5b66\u4f1a\u5229\u7528\u8fd9\u4e9b\u77e5\u8bc6\uff0c\u662f\u4e00\u4e2a\u590d\u6742\u7684\u95ee\u9898\u3002\u5e38\u8bc6\u63a8\u7406\u5bf9\u4e8e\u7406\u89e3\u8bed\u8a00\u4e5f\u81f3\u5173\u91cd\u8981\uff0c\u4f8b\u5982\u7406\u89e3\u201c\u4eba\u4e0d\u4f1a\u98de\u201d\u8fd9\u6837\u7684\u57fa\u672c\u5e38\u8bc6\u3002\u5f53\u524d\u7684NLP\u6a21\u578b\u5728\u663e\u5f0f\u5730\u5229\u7528\u548c\u63a8\u7406\u9886\u57df\u77e5\u8bc6\u53ca\u5e38\u8bc6\u65b9\u9762\u4ecd\u6709\u4e0d\u8db3\u3002<\/p>\n

                            NLP\u7684\u5e94\u7528\u573a\u666f<\/h2>\n

                            \u81ea\u7136\u8bed\u8a00\u5904\u7406\uff08NLP\uff09\u6280\u672f\u5df2\u7ecf\u5e7f\u6cdb\u5e94\u7528\u4e8e\u5404\u4e2a\u9886\u57df\uff0c\u6539\u53d8\u7740\u6211\u4eec\u4e0e\u6280\u672f\u7684\u4e92\u52a8\u65b9\u5f0f\uff0c\u6781\u5927\u5730\u63d0\u5347\u4e86\u4fe1\u606f\u83b7\u53d6\u548c\u5904\u7406\u7684\u6548\u7387\u3002\u53ef\u4ee5\u5206\u4e3a\u901a\u7528\u5e94\u7528\u548c\u7279\u5b9a\u884c\u4e1a\u5e94\u7528\u4e24\u5927\u7c7b\u3002<\/p>\n

                            \"\" <\/p>\n

                            NLP\u7684\u672a\u6765\u53d1\u5c55\u8d8b\u52bf<\/h2>\n
                            NLP\u6280\u672f\u5c06\u671d\u7740\u4ee5\u4e0b\u51e0\u4e2a\u4e3b\u8981\u8d8b\u52bf\u53d1\u5c55\uff1a<\/div>\n
                              \n
                            • \n
                              \u66f4\u5927\u3001\u66f4\u5f3a\u7684\u6a21\u578b\u4e0e\u66f4\u9ad8\u6548\u7684\u8bad\u7ec3\u63a8\u7406<\/strong>\uff1a\u5927\u578b\u8bed\u8a00\u6a21\u578b\uff08LLMs\uff09\u7684\u89c4\u6a21\u9884\u8ba1\u5c06\u7ee7\u7eed\u589e\u5927\uff0c\u7814\u7a76\u8005\u4eec\u4e5f\u5728\u63a2\u7d22\u66f4\u9ad8\u6548\u7684\u6a21\u578b\u67b6\u6784\u3001\u8bad\u7ec3\u7b97\u6cd5\u548c\u63a8\u7406\u6280\u672f\uff0c\u4ee5\u964d\u4f4e\u8ba1\u7b97\u6210\u672c\u548c\u80fd\u8017\uff0c\u4f7fLLMs\u80fd\u66f4\u5e7f\u6cdb\u5730\u90e8\u7f72\u548c\u5e94\u7528\u3002<\/div>\n<\/li>\n
                            • \n
                              \u591a\u6a21\u6001\u878d\u5408<\/strong>\uff1a\u672a\u6765\u7684NLP\u7cfb\u7edf\u5c06\u66f4\u52a0\u6ce8\u91cd\u5904\u7406\u548c\u7406\u89e3\u591a\u79cd\u6a21\u6001\u7684\u4fe1\u606f\uff0c\u5982\u6587\u672c\u3001\u56fe\u50cf\u3001\u8bed\u97f3\u3001\u89c6\u9891\u7b49\uff0c\u5b9e\u73b0\u66f4\u4e30\u5bcc\u3001\u66f4\u81ea\u7136\u7684\u4ea4\u4e92\u3002\u4f8b\u5982\uff0c\u80fd\u6839\u636e\u6587\u672c\u63cf\u8ff0\u751f\u6210\u56fe\u50cf\uff0c\u6216\u6839\u636e\u89c6\u9891\u5185\u5bb9\u751f\u6210\u6587\u672c\u6458\u8981\u3002<\/div>\n<\/li>\n
                            • \n
                              \u5e38\u8bc6\u63a8\u7406\u4e0e\u53ef\u89e3\u91ca\u6027<\/strong>\uff1a\u63d0\u5347\u6a21\u578b\u7684\u5e38\u8bc6\u63a8\u7406\u80fd\u529b\u548c\u53ef\u89e3\u91ca\u6027\u662fNLP\u9886\u57df\u7684\u91cd\u8981\u6311\u6218\u3002\u672a\u6765\u7684\u7814\u7a76\u5c06\u8ba9\u6a21\u578b\u4e0d\u4ec5\u80fd\u201c\u77e5\u5176\u7136\u201d\uff0c\u66f4\u80fd\u201c\u77e5\u5176\u6240\u4ee5\u7136\u201d\uff0c\u80fd\u57fa\u4e8e\u5e38\u8bc6\u8fdb\u884c\u903b\u8f91\u63a8\u7406\uff0c\u5bf9\u51b3\u7b56\u8fc7\u7a0b\u7ed9\u51fa\u5408\u7406\u89e3\u91ca\u3002<\/div>\n<\/li>\n
                            • \n
                              \u4e2a\u6027\u5316\u4e0e\u9886\u57df\u81ea\u9002\u5e94<\/strong>\uff1aNLP\u6a21\u578b\u5c06\u66f4\u52a0\u6ce8\u91cd\u4e2a\u6027\u5316\u548c\u9886\u57df\u81ea\u9002\u5e94\u6027\uff0c\u80fd\u6839\u636e\u7528\u6237\u7684\u7279\u5b9a\u9700\u6c42\u3001\u504f\u597d\u4ee5\u53ca\u4e0d\u540c\u9886\u57df\u7684\u77e5\u8bc6\u7279\u70b9\u8fdb\u884c\u8c03\u6574\u548c\u4f18\u5316\uff0c\u63d0\u4f9b\u66f4\u7cbe\u51c6\u3001\u66f4\u8d34\u5207\u7684\u670d\u52a1\u3002<\/div>\n<\/li>\n
                            • \n
                              \u4f4e\u8d44\u6e90\u4e0e\u53ef\u4fe1NLP<\/strong>\uff1a\u9488\u5bf9\u4f4e\u8d44\u6e90\u8bed\u8a00\u548c\u5c0f\u6837\u672c\u5b66\u4e60\u573a\u666f\u7684NLP\u6280\u672f\u5c06\u6301\u7eed\u53d1\u5c55\u3002\u786e\u4fddNLP\u6a21\u578b\u7684\u516c\u5e73\u6027\u3001\u9c81\u68d2\u6027\u3001\u5b89\u5168\u6027\u548c\u9690\u79c1\u4fdd\u62a4\uff08\u5373\u53ef\u4fe1NLP\uff09\u4e5f\u5c06\u6210\u4e3a\u7814\u7a76\u7684\u91cd\u70b9\uff0c\u5e94\u5bf9\u6a21\u578b\u53ef\u80fd\u4ea7\u751f\u7684\u504f\u89c1\u3001\u9519\u8bef\u4fe1\u606f\u548c\u6ee5\u7528\u98ce\u9669\u3002<\/div>\n<\/li>\n
                            • \n
                              \u4e0e\u77e5\u8bc6\u56fe\u8c31\u7684\u6df1\u5ea6\u878d\u5408<\/strong>\uff1a\u5c06NLP\u4e0e\u77e5\u8bc6\u56fe\u8c31\u7b49\u7b26\u53f7\u77e5\u8bc6\u8868\u793a\u65b9\u6cd5\u66f4\u7d27\u5bc6\u5730\u7ed3\u5408\u8d77\u6765\uff0c\u6709\u671b\u63d0\u5347\u6a21\u578b\u7684\u77e5\u8bc6\u5229\u7528\u80fd\u529b\u548c\u63a8\u7406\u80fd\u529b\uff0c\u5b9e\u73b0\u66f4\u6df1\u5c42\u6b21\u7684\u8bed\u8a00\u7406\u89e3\u3002<\/div>\n<\/li>\n<\/ul>\n

                              \"\" <\/p>\n

                              \u968f\u7740\u6280\u672f\u7684\u4e0d\u65ad\u8fdb\u6b65\uff0cNLP\u5c06\u5728\u66f4\u591a\u9886\u57df\u53d1\u6325\u5173\u952e\u4f5c\u7528\uff0c\u63a8\u52a8\u4eba\u5de5\u667a\u80fd\u5411\u66f4\u9ad8\u5c42\u6b21\u7684\u667a\u80fd\u8fc8\u8fdb\uff0c\u8ba9\u4eba\u4e0e\u673a\u5668\u7684\u4ea4\u6d41\u66f4\u52a0\u667a\u80fd\u3001\u81ea\u7136\u548c\u9ad8\u6548\u3002\u5bf9\u4e8e\u666e\u901a\u7528\u6237\u800c\u8a00\uff0c\u7406\u89e3NLP\u7684\u57fa\u672c\u6982\u5ff5\u548c\u53d1\u5c55\u8d8b\u52bf\uff0c\u5c06\u6709\u52a9\u4e8e\u66f4\u597d\u5730\u5229\u7528\u548c\u9002\u5e94\u8fd9\u4e2a\u7531AI\u9a71\u52a8\u7684\u8bed\u8a00\u667a\u80fd\u65f6\u4ee3\u3002<\/p>\n<\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

                              \u81ea\u7136\u8bed\u8a00\u5904\u7406\uff08NLP\uff09\u662f\u4eba\u5de5\u667a\u80fd\u7684\u4e00\u4e2a\u5206\u652f\uff0c\u8ba9\u8ba1\u7b97\u673a\u80fd\u7406\u89e3\u3001\u89e3\u91ca\u548c\u751f\u6210\u4eba\u7c7b\u8bed\u8a00\u3002\u901a\u8fc7\u4e00\u7cfb\u5217\u6280\u672f\uff0c\u5982\u5206\u8bcd\u3001\u8bcd\u6027\u6807\u6ce8\u3001\u547d\u540d\u5b9e\u4f53\u8bc6\u522b\u3001\u8bcd\u5d4c\u5165\u3001\u673a\u5668\u7ffb\u8bd1\u548c\u60c5\u611f\u5206\u6790\u7b49\uff0c\u7ed3\u5408\u4ece\u4f20\u7edf\u7edf\u8ba1\u65b9\u6cd5\u5230\u73b0\u4ee3\u6df1\u5ea6\u5b66\u4e60\u6a21\u578b\uff08\u5982BERT\u3001GPT\u7cfb\u5217\u548c\u5927\u578b\u8bed\u8a00\u6a21\u578bLLMs\uff09\u7684\u7b97\u6cd5\uff0c\u5b9e\u73b0\u4e0e\u4eba\u7c7b\u8bed\u8a00\u7684\u4ea4\u4e92\u3002 \u4ec0\u4e48\u662f\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff1f \u81ea\u7136\u8bed\u8a00\u5904\u7406\uff08Natural Language Processing, NLP\uff09\u662f\u4eba\u5de5\u667a\u80fd\uff08AI\uff09\u548c\u8ba1\u7b97\u673a\u79d1\u5b66\u9886\u57df\u7684\u4e00\u4e2a\u5173\u952e\u5206\u652f\uff0c\u6838\u5fc3\u76ee\u6807\u662f\u8ba9\u8ba1\u7b97\u673a\u80fd\u7406\u89e3\u3001\u89e3\u91ca\u3001\u64cd\u4f5c\u5e76\u6700\u7ec8\u751f\u6210\u4eba\u7c7b\u8bed\u8a00\u3002 \u6253\u7834\u4eba\u4e0e\u673a\u5668\u4e4b\u95f4\u7684\u8bed\u8a00\u969c\u788d\uff0c\u4f7f\u8ba1\u7b97\u673a\u80fd\u50cf\u4eba\u7c7b\u4e00\u6837\u5904\u7406\u548c\u5206\u6790\u6211\u4eec\u6240\u4f7f\u7528\u7684\u8bed\u8a00\uff0c\u65e0\u8bba\u662f\u6587\u672c\u8fd8\u662f\u8bed\u97f3 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