{
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        "author": "isnowfy",
        "author_email": "UNKNOWN",
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            "Development Status :: 3 - Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
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        "description": "#SnowNLP: Simplified Chinese Text Processing\n\nSnowNLP\u662f\u4e00\u4e2apython\u5199\u7684\u7c7b\u5e93\uff0c\u53ef\u4ee5\u65b9\u4fbf\u7684\u5904\u7406\u4e2d\u6587\u6587\u672c\u5185\u5bb9\uff0c\u662f\u53d7\u5230\u4e86[TextBlob](https://github.com/sloria/TextBlob)\u7684\u542f\u53d1\u800c\u5199\u7684\uff0c\u7531\u4e8e\u73b0\u5728\u5927\u90e8\u5206\u7684\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5e93\u57fa\u672c\u90fd\u662f\u9488\u5bf9\u82f1\u6587\u7684\uff0c\u4e8e\u662f\u5199\u4e86\u4e00\u4e2a\u65b9\u4fbf\u5904\u7406\u4e2d\u6587\u7684\u7c7b\u5e93\uff0c\u5e76\u4e14\u548cTextBlob\u4e0d\u540c\u7684\u662f\uff0c\u8fd9\u91cc\u6ca1\u6709\u7528NLTK\uff0c\u6240\u6709\u7684\u7b97\u6cd5\u90fd\u662f\u81ea\u5df1\u5b9e\u73b0\u7684\uff0c\u5e76\u4e14\u81ea\u5e26\u4e86\u4e00\u4e9b\u8bad\u7ec3\u597d\u7684\u5b57\u5178\u3002\u6ce8\u610f\u672c\u7a0b\u5e8f\u90fd\u662f\u5904\u7406\u7684unicode\u7f16\u7801\uff0c\u6240\u4ee5\u4f7f\u7528\u65f6\u8bf7\u81ea\u884cdecode\u6210unicode\u3002\n\n~~~~{python}\nfrom snownlp import SnowNLP\n\ns = SnowNLP(u'\u8fd9\u4e2a\u4e1c\u897f\u771f\u5fc3\u5f88\u8d5e')\n\ns.words         # [u'\u8fd9\u4e2a', u'\u4e1c\u897f', u'\u771f\u5fc3',\n                #  u'\u5f88', u'\u8d5e']\n\ns.tags          # [(u'\u8fd9\u4e2a', u'r'), (u'\u4e1c\u897f', u'n'),\n                #  (u'\u771f\u5fc3', u'd'), (u'\u5f88', u'd'),\n                #  (u'\u8d5e', u'Vg')]\n\ns.sentiments    # 0.9769663402895832 positive\u7684\u6982\u7387\n\ns.pinyin        # [u'zhe', u'ge', u'dong', u'xi',\n                #  u'zhen', u'xin', u'hen', u'zan']\n\ns = SnowNLP(u'\u300c\u7e41\u9ad4\u5b57\u300d\u300c\u7e41\u9ad4\u4e2d\u6587\u300d\u7684\u53eb\u6cd5\u5728\u81fa\u7063\u4ea6\u5f88\u5e38\u898b\u3002')\n\ns.han           # u'\u300c\u7e41\u4f53\u5b57\u300d\u300c\u7e41\u4f53\u4e2d\u6587\u300d\u7684\u53eb\u6cd5\n                # \u5728\u53f0\u6e7e\u4ea6\u5f88\u5e38\u89c1\u3002'\n\ntext = u'''\n\u81ea\u7136\u8bed\u8a00\u5904\u7406\u662f\u8ba1\u7b97\u673a\u79d1\u5b66\u9886\u57df\u4e0e\u4eba\u5de5\u667a\u80fd\u9886\u57df\u4e2d\u7684\u4e00\u4e2a\u91cd\u8981\u65b9\u5411\u3002\n\u5b83\u7814\u7a76\u80fd\u5b9e\u73b0\u4eba\u4e0e\u8ba1\u7b97\u673a\u4e4b\u95f4\u7528\u81ea\u7136\u8bed\u8a00\u8fdb\u884c\u6709\u6548\u901a\u4fe1\u7684\u5404\u79cd\u7406\u8bba\u548c\u65b9\u6cd5\u3002\n\u81ea\u7136\u8bed\u8a00\u5904\u7406\u662f\u4e00\u95e8\u878d\u8bed\u8a00\u5b66\u3001\u8ba1\u7b97\u673a\u79d1\u5b66\u3001\u6570\u5b66\u4e8e\u4e00\u4f53\u7684\u79d1\u5b66\u3002\n\u56e0\u6b64\uff0c\u8fd9\u4e00\u9886\u57df\u7684\u7814\u7a76\u5c06\u6d89\u53ca\u81ea\u7136\u8bed\u8a00\uff0c\u5373\u4eba\u4eec\u65e5\u5e38\u4f7f\u7528\u7684\u8bed\u8a00\uff0c\n\u6240\u4ee5\u5b83\u4e0e\u8bed\u8a00\u5b66\u7684\u7814\u7a76\u6709\u7740\u5bc6\u5207\u7684\u8054\u7cfb\uff0c\u4f46\u53c8\u6709\u91cd\u8981\u7684\u533a\u522b\u3002\n\u81ea\u7136\u8bed\u8a00\u5904\u7406\u5e76\u4e0d\u662f\u4e00\u822c\u5730\u7814\u7a76\u81ea\u7136\u8bed\u8a00\uff0c\n\u800c\u5728\u4e8e\u7814\u5236\u80fd\u6709\u6548\u5730\u5b9e\u73b0\u81ea\u7136\u8bed\u8a00\u901a\u4fe1\u7684\u8ba1\u7b97\u673a\u7cfb\u7edf\uff0c\n\u7279\u522b\u662f\u5176\u4e2d\u7684\u8f6f\u4ef6\u7cfb\u7edf\u3002\u56e0\u800c\u5b83\u662f\u8ba1\u7b97\u673a\u79d1\u5b66\u7684\u4e00\u90e8\u5206\u3002\n'''\n\ns = SnowNLP(text)\n\ns.keywords(3)\t# [u'\u8bed\u8a00', u'\u81ea\u7136', u'\u8ba1\u7b97\u673a']\n\ns.summary(3)\t# [u'\u56e0\u800c\u5b83\u662f\u8ba1\u7b97\u673a\u79d1\u5b66\u7684\u4e00\u90e8\u5206',\n                #  u'\u81ea\u7136\u8bed\u8a00\u5904\u7406\u662f\u4e00\u95e8\u878d\u8bed\u8a00\u5b66\u3001\u8ba1\u7b97\u673a\u79d1\u5b66\u3001\n\t\t\t\t#\t \u6570\u5b66\u4e8e\u4e00\u4f53\u7684\u79d1\u5b66',\n\t\t\t\t#  u'\u81ea\u7136\u8bed\u8a00\u5904\u7406\u662f\u8ba1\u7b97\u673a\u79d1\u5b66\u9886\u57df\u4e0e\u4eba\u5de5\u667a\u80fd\n\t\t\t\t#\t \u9886\u57df\u4e2d\u7684\u4e00\u4e2a\u91cd\u8981\u65b9\u5411']\ns.sentences\n\ns = SnowNLP([[u'\u8fd9\u7bc7', u'\u6587\u7ae0'],\n             [u'\u90a3\u7bc7', u'\u8bba\u6587'],\n             [u'\u8fd9\u4e2a']])\ns.tf\ns.idf\ns.sim([u'\u6587\u7ae0'])# [0.3756070762985226, 0, 0]\n~~~~\n\n## Features\n\n* \u4e2d\u6587\u5206\u8bcd\uff08[Character-Based Generative Model](http://aclweb.org/anthology//Y/Y09/Y09-2047.pdf)\uff09\n* \u8bcd\u6027\u6807\u6ce8\uff08[TnT](http://aclweb.org/anthology//A/A00/A00-1031.pdf) 3-gram \u9690\u9a6c\uff09\n* \u60c5\u611f\u5206\u6790\uff08\u73b0\u5728\u8bad\u7ec3\u6570\u636e\u4e3b\u8981\u662f\u4e70\u5356\u4e1c\u897f\u65f6\u7684\u8bc4\u4ef7\uff0c\u6240\u4ee5\u5bf9\u5176\u4ed6\u7684\u4e00\u4e9b\u53ef\u80fd\u6548\u679c\u4e0d\u662f\u5f88\u597d\uff0c\u5f85\u89e3\u51b3\uff09\n* \u6587\u672c\u5206\u7c7b\uff08Naive Bayes\uff09\n* \u8f6c\u6362\u6210\u62fc\u97f3\uff08Trie\u6811\u5b9e\u73b0\u7684\u6700\u5927\u5339\u914d\uff09\n* \u7e41\u4f53\u8f6c\u7b80\u4f53\uff08Trie\u6811\u5b9e\u73b0\u7684\u6700\u5927\u5339\u914d\uff09\n* \u63d0\u53d6\u6587\u672c\u5173\u952e\u8bcd\uff08[TextRank](http://acl.ldc.upenn.edu/acl2004/emnlp/pdf/Mihalcea.pdf)\u7b97\u6cd5\uff09\n* \u63d0\u53d6\u6587\u672c\u6458\u8981\uff08[TextRank](http://acl.ldc.upenn.edu/acl2004/emnlp/pdf/Mihalcea.pdf)\u7b97\u6cd5\uff09\n* tf\uff0cidf\n* Tokenization\uff08\u5206\u5272\u6210\u53e5\u5b50\uff09\n* \u6587\u672c\u76f8\u4f3c\uff08[BM25](http://en.wikipedia.org/wiki/Okapi_BM25)\uff09\n* \u652f\u6301python3\uff08\u611f\u8c22[erning](https://github.com/erning)\uff09\n\n## Get It now\n\n~~~~\n$ pip install snownlp\n~~~~\n\n## \u5173\u4e8e\u8bad\u7ec3\n\n\u73b0\u5728\u63d0\u4f9b\u8bad\u7ec3\u7684\u5305\u62ec\u5206\u8bcd\uff0c\u8bcd\u6027\u6807\u6ce8\uff0c\u60c5\u611f\u5206\u6790\uff0c\u800c\u4e14\u90fd\u63d0\u4f9b\u4e86\u6211\u7528\u6765\u8bad\u7ec3\u7684\u539f\u59cb\u6587\u4ef6\n\u4ee5\u5206\u8bcd\u4e3a\u4f8b\n\u5206\u8bcd\u5728`snownlp/seg`\u76ee\u5f55\u4e0b\n~~~~{python}\nfrom snownlp import seg\nseg.train('data.txt')\nseg.save('seg.marshal')\n#from snownlp import tag\n#tag.train('199801.txt')\n#tag.save('tag.marshal')\n#from snownlp import sentiment\n#sentiment.train('neg.txt', 'pos.txt')\n#sentiment.save('sentiment.marshal')\n~~~~\n\u8fd9\u6837\u8bad\u7ec3\u597d\u7684\u6587\u4ef6\u5c31\u5b58\u50a8\u4e3a`seg.marshal`\u4e86\uff0c\u4e4b\u540e\u4fee\u6539`snownlp/seg/__init__.py`\u91cc\u7684`data_path`\u6307\u5411\u521a\u8bad\u7ec3\u597d\u7684\u6587\u4ef6\u5373\u53ef\n\n## License\n\nMIT licensed.\n",
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