Summ_Sumy_luhn.ipynb

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   "source": [
    "import os\n",
    "from sumy.summarizers.luhn import LuhnSummarizer \n",
    "from sumy.parsers.plaintext import PlaintextParser\n",
    "from sumy.nlp.tokenizers import Tokenizer\n",
    "from sumy.nlp.stemmers import Stemmer\n",
    "from sumy.utils import get_stop_words"
   ]
  },
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   "cell_type": "code",
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    "LANGUAGE = \"english\"\n",
    "SENTENCES_COUNT = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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   "source": [
    "for file in os.listdir('topics'):\n",
    "    with open('topics/' + file, 'r') as f:\n",
    "        parser = PlaintextParser.from_string(unicode(f.read().replace('\\n',' '), errors='ignore'), Tokenizer(LANGUAGE))\n",
    "        stemmer = Stemmer(LANGUAGE)\n",
    "        summarizer = LuhnSummarizer(stemmer)\n",
    "        summarizer.stop_words = get_stop_words(LANGUAGE)\n",
    "        with open('summ_sumy_lex/' + file.split('.')[0] + '.txt', 'w') as fw:\n",
    "            for sentence in summarizer(parser.document, SENTENCES_COUNT):\n",
    "                #print sentence\n",
    "                fw.writelines(str(sentence))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "While summarizing a document, summarizer invokes __call__() method which takes two arguments, a document and Sentence_Count. The second argument doesn't seem to be effective while summarizing the document. Even with SENTENCE_COUNT = 1 summaries generated have more than 1 sentence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
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   "outputs": [],
   "source": []
  }
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