2020\u5e743\u670811\u65e5\uff0c\u5546\u4e1a\u4eba\u5de5\u667a\u80fd\u9886\u57df\u9886\u519b\u8005IBM\u5ba3\u5e03\u63a8\u51fa\u51e0\u9879\u5168\u65b0\u7684IBMWatson \u6280\u672f\uff0c\u65e8\u5728\u5e2e\u52a9\u7ec4\u7ec7\u673a\u6784\u66f4\u6e05\u6670\u5730\u8bc6\u522b\u3001\u7406\u89e3\u548c\u5206\u6790\u82f1\u8bed\u8bed\u8a00\u4e2d\u67d0\u4e9b\u6700\u5177\u6311\u6218\u6027\u7684\u65b9\u9762\uff0c\u4ece\u800c\u83b7\u53d6\u66f4\u591a\u6d1e\u5bdf\u3002<\/p>\n
\u5168\u65b0\u7684IBMWatson \u6280\u672f\u4ee3\u8868\u7740ProjectDebater \u6240\u63d0\u4f9b\u7684\u5173\u952e\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff08NaturalLanguage Processing\uff0cNLP\uff09\u80fd\u529b\u9996\u6b21\u5b9e\u73b0\u5546\u4e1a\u5316\uff0cProjectDebater \u7531IBM\u7814\u7a76\u9662\uff08IBMResearch\uff09\u7814\u53d1\uff0c\u662f\u76ee\u524d\u552f\u4e00\u4e00\u4e2a\u80fd\u591f\u5c31\u590d\u6742\u8bdd\u9898\u4e0e\u4eba\u7c7b\u5c55\u5f00\u8fa9\u8bba\u7684\u4eba\u5de5\u667a\u80fd\u7cfb\u7edf\u3002\u5728\u6b64\u6b21\u63a8\u51fa\u7684\u6280\u672f\u4e2d\uff0cIBM\u9996\u6b21\u754c\u5b9a\u4e86\u4e00\u9879\u65b0\u578b\u9ad8\u7ea7\u60c5\u7eea\u5206\u6790\u80fd\u529b\uff0c\u4ee5\u8bc6\u522b\u53ca\u5206\u6790\u4e60\u60ef\u7528\u8bed\u548c\u53e3\u8bed\u5316\u8868\u8fbe\u3002\u5bf9\u4e8e\u4eba\u5de5\u667a\u80fd\u7cfb\u7edf\u800c\u8a00\uff0c\u8bc6\u522b\u8bf8\u5982“hardlyhelpful\uff08\u51e0\u4e4e\u6ca1\u6709\u5e2e\u52a9\uff09”\u6216“hotunder the collar\uff08\u6012\u6c14\u51b2\u5929\uff09”\u4e4b\u7c7b\u7684\u77ed\u8bed\u4e00\u76f4\u662f\u4e00\u9879\u6311\u6218\uff0c\u56e0\u4e3a\u5b83\u4eec\u96be\u4ee5\u88ab\u7b97\u6cd5\u8bc6\u522b\u3002\u901a\u8fc7\u9ad8\u7ea7\u60c5\u7eea\u5206\u6790\uff0c\u4f01\u4e1a\u53ef\u4ee5\u4f7f\u7528Watson\u5e94\u7528\u7a0b\u5e8f\u63a5\u53e3\uff08API\uff09\u6765\u5206\u6790\u6b64\u7c7b\u8bed\u8a00\u6570\u636e\uff0c\u4ece\u800c\u66f4\u5168\u9762\u5730\u4e86\u89e3\u81ea\u8eab\u8fd0\u8425\u60c5\u51b5\u3002\u6b64\u5916\uff0cIBM\u8fd8\u5c06IBM\u7814\u7a76\u9662\u7684\u6280\u672f\u5e94\u7528\u4e8e\u7406\u89e3\u8bf8\u5982PDF\u6587\u6863\u548c\u5408\u540c\u4e4b\u7c7b\u7684\u5546\u4e1a\u6587\u6863\uff0c\u5e76\u5c06\u8fd9\u4e9b\u6280\u672f\u6dfb\u52a0\u5230IBM\u4eba\u5de5\u667a\u80fd\u6a21\u578b\u5f53\u4e2d\u3002<\/p>\n
IBMData and AI\u603b\u7ecf\u7406RobThomas \u8868\u793a\uff0c“\u8bed\u8a00\u65e2\u662f\u8868\u8fbe\u601d\u60f3\u548c\u89c2\u70b9\u7684\u5de5\u5177\uff0c\u4e5f\u662f\u4f20\u9012\u4fe1\u606f\u7684\u5de5\u5177\u3002\u6b63\u56e0\u5982\u6b64\uff0c\u6211\u4eec\u5c06ProjectDebater\u4e2d\u83b7\u53d6\u7684\u6280\u672f\u96c6\u6210\u5230Watson\uff0c\u6211\u4eec\u76f8\u4fe1NLP\u5c06\u589e\u5f3a\u4f01\u4e1a\u4ece\u4eba\u7c7b\u8bed\u8a00\u4e2d\u91c7\u96c6\u3001\u5206\u6790\u548c\u7406\u89e3\u4fe1\u606f\u7684\u80fd\u529b\uff0c\u8fd9\u5c06\u6709\u52a9\u4e8e\u4f01\u4e1a\u66f4\u597d\u5730\u5229\u7528\u8574\u542b\u5728\u6570\u636e\u4e2d\u7684\u667a\u6167\u8d44\u4ea7\u3002”<\/p>\n
\u4eca\u5929\uff0cIBM\u5ba3\u5e03\uff0c\u8ba1\u5212\u5c06\u5728\u5168\u5e74\u81f4\u529b\u4e8e\u5c06ProjectDebater \u6280\u672f\u96c6\u6210\u81f3Watson\uff0c\u5e76\u4fa7\u91cd\u4e8e\u63d0\u9ad8\u5ba2\u6237\u4f7f\u7528\u81ea\u7136\u8bed\u8a00\u7684\u80fd\u529b\uff1a<\/p>\n
\u5206\u6790—\u9ad8\u7ea7\u60c5\u7eea\u5206\u6790\uff08Advanced Sentiment Analysis\uff09\u3002IBM \u589e\u5f3a\u4e86\u60c5\u7eea\u5206\u6790\u80fd\u529b\uff0c\u80fd\u591f\u66f4\u597d\u5730\u8bc6\u522b\u548c\u7406\u89e3\u590d\u6742\u7684\u5355\u8bcd\u7ec4\u5408\uff0c\u6bd4\u5982\u50cf\u5305\u542b\u77ed\u8bed\u548c\u8868\u8fbe\u7684\u4e60\u60ef\u7528\u8bed\u4ee5\u53ca\u6240\u8c13\u7684\u60c5\u7eea\u8f6c\u6362\u8bcd\u7ec4\uff08sentiment shifter\uff09\uff0c\u5373\u7531\u4e0d\u540c\u5355\u8bcd\u7ec4\u6210\u4f46\u5374\u5448\u73b0\u65b0\u542b\u4e49\u7684\u5355\u8bcd\u7ec4\u5408\uff0c\u4f8b\u5982“hardly helpful\uff08\u51e0\u4e4e\u6ca1\u6709\u5e2e\u52a9\uff09”\u3002\u8be5\u6280\u672f\u5c06\u4e8e\u672c\u6708\u6574\u5408\u81f3Watson Natural Language Understanding \u3002\u6b64\u5916\uff0c\u6211\u4eec\u8fd8\u5ba3\u5e03\u4e86\u4e00\u9879\u65b0\u7684\u5206\u7c7b\u6280\u672f\uff0c\u501f\u52a9\u8be5\u6280\u672f\uff0c\u5ba2\u6237\u5c06\u80fd\u521b\u5efa\u4eba\u5de5\u667a\u80fd\u6a21\u578b\uff0c\u66f4\u8f7b\u677e\u5730\u5206\u7c7b\u91c7\u8d2d\u5408\u540c\u7b49\u5546\u4e1a\u6587\u6863\u4e2d\u51fa\u73b0\u7684\u6761\u6b3e\u3002\u5229\u7528Project Debater \u4e2d\u7684\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u5206\u7c7b\u6280\u672f\uff08deep learning-based classification technology\uff09\uff0c\u8be5\u65b0\u80fd\u529b\u53ef\u4ece\u4ec5\u6570\u767e\u4e2a\u793a\u4f8b\u4e2d\u5b66\u4e60\uff0c\u8fdb\u800c\u5feb\u901f\u3001\u8f7b\u677e\u5730\u6267\u884c\u65b0\u5206\u7c7b\u3002\u8be5\u6280\u672f\u8ba1\u5212\u5c06\u4e8e\u4eca\u5e74\u665a\u4e9b\u65f6\u5019\u6dfb\u52a0\u81f3 Watson Discovery\u3002<\/p>\n
\u6458\u8981\u63d0\u70bc—\u603b\u7ed3\uff08Summarization\uff09\u3002\u8be5\u6280\u672f\u53ef\u4ece\u5404\u79cd\u6765\u6e90\u4e2d\u63d0\u53d6\u6587\u672c\u6570\u636e\uff0c\u4e3a\u7528\u6237\u5c31\u4e0e\u7279\u5b9a\u4e3b\u9898\u76f8\u5173\u7684\u53e3\u5934\u548c\u4e66\u9762\u8a00\u8bba\u63d0\u70bc\u4e00\u4efd\u6458\u8981\u3002\u4eca\u5e74\u7684\u683c\u83b1\u7f8e\u9881\u5956\u793c\u901a\u8fc7Summarization \u7684\u4e00\u4e2a\u65e9\u671f\u7248\u672c\u5206\u6790\u4e86\u8d85\u8fc7 1,800 \u4e07\u7bc7\u6587\u7ae0\u3001\u535a\u5ba2\u548c\u4e2a\u4eba\u6863\u6848\uff0c\u4ee5\u63d0\u70bc\u5173\u4e8e\u6570\u767e\u540d\u683c\u83b1\u7f8e\u827a\u672f\u5bb6\u548c\u540d\u4eba\u7684\u7ec6\u5fae\u6d1e\u5bdf\u3002\u968f\u540e\uff0c\u8be5\u6570\u636e\u88ab\u5e94\u7528\u5230 www.grammy.com \u7684\u7ea2\u6bef\u89c6\u9891\u76f4\u64ad\u3001\u70b9\u64ad\u89c6\u9891\u4ee5\u53ca\u7167\u7247\u4e2d\uff0c\u5e2e\u52a9\u7c89\u4e1d\u66f4\u6df1\u5165\u5730\u4e86\u89e3\u5f53\u665a\u4e3b\u8981\u8bdd\u9898\u7684\u80cc\u666f\u4fe1\u606f\u3002\u8be5\u6280\u672f\u8ba1\u5212\u5c06\u4e8e\u4eca\u5e74\u665a\u4e9b\u65f6\u5019\u88ab\u6dfb\u52a0\u81f3 IBM Watson Natural Language Understanding \u3002<\/p>\n
\u805a\u7c7b—\u9ad8\u7ea7\u4e3b\u9898\u805a\u7c7b\uff08Advanced Topic Clustering\uff09\u3002\u57fa\u4e8e\u4ece Project Debater \u83b7\u5f97\u7684\u6d1e\u5bdf\uff0c\u5168\u65b0\u4e3b\u9898\u805a\u7c7b\u6280\u672f\u5c06\u652f\u6301\u7528\u6237\u5bf9\u8f93\u5165\u7684\u6570\u636e\u8fdb\u884c“\u805a\u7c7b”\uff0c\u4ece\u800c\u5c31\u76f8\u5173\u4fe1\u606f\u521b\u5efa\u6709\u610f\u4e49\u7684“\u4e3b\u9898”\uff0c\u7528\u6237\u968f\u540e\u5373\u53ef\u5bf9\u8fd9\u4e9b\u4e3b\u9898\u8fdb\u884c\u5206\u6790\u3002\u8fd9\u9879\u8ba1\u5212\u5c06\u4e8e\u4eca\u5e74\u665a\u4e9b\u65f6\u5019\u6574\u5408\u81f3 Watson Discovery \u7684\u6280\u672f\uff0c\u8fd8\u5c06\u652f\u6301\u4e3b\u9898\u4e13\u5bb6\u5bf9\u4e3b\u9898\u8fdb\u884c\u5b9a\u5236\u548c\u5fae\u8c03\uff0c\u4ee5\u53cd\u6620\u7279\u5b9a\u4f01\u4e1a\u6216\u884c\u4e1a\u7684\u8bed\u8a00\u98ce\u683c\uff0c\u4f8b\u5982\u4fdd\u9669\u3001\u533b\u7597\u5065\u5eb7\u548c\u5236\u9020\u884c\u4e1a\u3002<\/p>\n
IBM\u957f\u671f\u4ee5\u6765\u4e00\u76f4\u662fNLP\u9886\u57df\u7684\u9886\u519b\u8005\uff0c\u81f4\u529b\u4e8e\u5f00\u53d1\u6280\u672f\u4ee5\u652f\u6301\u8ba1\u7b97\u673a\u7cfb\u7edf\u66f4\u51c6\u786e\u3001\u66f4\u5feb\u901f\u5730\u5b66\u4e60\u3001\u5206\u6790\u53ca\u7406\u89e3\u4eba\u7c7b\u8bed\u8a00\uff0c\u5305\u62ec\u611f\u60c5\u8272\u5f69\u3001\u65b9\u8a00\u3001\u8bed\u8c03\u7b49\u7b49\u3002IBM\u5df2\u901a\u8fc7Watson\u5c06\u5176NLP\u6280\u672f\u63a8\u5411\u5e02\u573a\uff0c\u5176\u4e2d\u5927\u90e8\u5206\u7531IBM\u7814\u7a76\u9662\u7814\u53d1\uff0c\u4f8b\u5982\uff0c\u7528\u4e8e\u6587\u4e66\u7406\u89e3\u7684WatsonDiscovery\u3001\u7528\u4e8e\u865a\u62df\u4ee3\u7406\u7684IBMWatson Assistant\u4ee5\u53ca\u7528\u4e8e\u9ad8\u7ea7\u60c5\u7eea\u5206\u6790\u7684WatsonNatural Language Understanding\u3002<\/p>\n
ESPNFantasy Football\u4f7f\u7528WatsonDiscovery\u548cWatsonKnowledge Studio\u5206\u6790\u8d5b\u5b63\u4e2d\u6bcf\u5929\u4ea7\u751f\u7684\u6570\u4ee5\u767e\u4e07\u8ba1\u7684\u8db3\u7403\u6570\u636e\u6765\u6e90\uff0c\u4ee5\u63d0\u4f9b\u5173\u4e8eFantasyFootball\u8fd0\u52a8\u5458\u7684\u6570\u767e\u4e07\u4e2a\u5b9e\u65f6\u6d1e\u5bdf\u3002\u901a\u8fc7\u81ea\u7136\u8bed\u8a00\u5904\u7406\uff0cWatson\u53ef\u4ee5\u8bc6\u522b\u5305\u62ec\u65b0\u95fb\u6587\u7ae0\u3001\u535a\u5ba2\u3001\u8bba\u575b\u3001\u6392\u540d\u3001\u9884\u6d4b\u3001\u64ad\u5ba2\u548c\u63a8\u7279\u7b49\u5185\u5bb9\u7684\u8bed\u6c14\u548c\u60c5\u7eea\uff0c\u6db5\u76d6\u4e86\u4ece\u66f4\u8863\u5ba4\u6d1e\u5bdf\u5230\u4f24\u75c5\u5206\u6790\u7b49\u5168\u65b9\u4f4d\u7684\u5185\u5bb9\u3002ESPNFantasyFootball\u5728\u7403\u5458\u5361\u4e2d\u5c55\u793a\u4e86\u8fd9\u4e9b\u6d1e\u89c1\uff0c\u8fd9\u4e9b\u7403\u5458\u5361\u8bb0\u5f55\u4e86\u6bcf\u4e2a\u7403\u5458\u7684\u5347\/\u964d\u7ea7\uff08Boom\/Bust\uff09\u6f5c\u529b\uff0c\u4ee5\u53ca“\u7403\u5458\u7684\u5173\u952e\u7403\u80fd\u529b\uff08PlayerBuzz\uff09”\u90e8\u5206\uff0c\u5b83\u603b\u7ed3\u4e86\u6709\u5173\u4e00\u540d\u7403\u5458\u7684\u6b63\u9762\u6216\u8d1f\u9762\u8bc4\u8bba\u3002<\/p>\n
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