text-summarization.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Text Summarization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using matplotlib backend: MacOSX\n"
     ]
    }
   ],
   "source": [
    "import re\n",
    "import string\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from nltk import pos_tag\n",
    "from nltk.tokenize import sent_tokenize, word_tokenize\n",
    "from nltk.stem.wordnet import WordNetLemmatizer\n",
    "from nltk.corpus.reader.wordnet import NOUN, VERB, ADJ, ADV\n",
    "from nltk.corpus import brown, stopwords\n",
    "from nltk.cluster.util import cosine_distance\n",
    "from operator import itemgetter\n",
    "%matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentences = brown.sents('ca01')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "98"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(sentences)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[\"The Fulton County Grand Jury said Friday an investigation of Atlanta's recent primary election produced `` no evidence '' that any irregularities took place .\",\n",
       " \"The jury further said in term-end presentments that the City Executive Committee , which had over-all charge of the election , `` deserves the praise and thanks of the City of Atlanta '' for the manner in which the election was conducted .\",\n",
       " \"The September-October term jury had been charged by Fulton Superior Court Judge Durwood Pye to investigate reports of possible `` irregularities '' in the hard-fought primary which was won by Mayor-nominate Ivan Allen Jr. .\",\n",
       " \"`` Only a relative handful of such reports was received '' , the jury said , `` considering the widespread interest in the election , the number of voters and the size of this city '' .\",\n",
       " \"The jury said it did find that many of Georgia's registration and election laws `` are outmoded or inadequate and often ambiguous '' .\",\n",
       " \"It recommended that Fulton legislators act `` to have these laws studied and revised to the end of modernizing and improving them '' .\",\n",
       " \"The grand jury commented on a number of other topics , among them the Atlanta and Fulton County purchasing departments which it said `` are well operated and follow generally accepted practices which inure to the best interest of both governments '' .\",\n",
       " 'Merger proposed',\n",
       " \"However , the jury said it believes `` these two offices should be combined to achieve greater efficiency and reduce the cost of administration '' .\",\n",
       " \"The City Purchasing Department , the jury said , `` is lacking in experienced clerical personnel as a result of city personnel policies '' .\",\n",
       " \"It urged that the city `` take steps to remedy '' this problem .\",\n",
       " \"Implementation of Georgia's automobile title law was also recommended by the outgoing jury .\",\n",
       " \"It urged that the next Legislature `` provide enabling funds and re-set the effective date so that an orderly implementation of the law may be effected '' .\",\n",
       " \"The grand jury took a swipe at the State Welfare Department's handling of federal funds granted for child welfare services in foster homes .\",\n",
       " \"`` This is one of the major items in the Fulton County general assistance program '' , the jury said , but the State Welfare Department `` has seen fit to distribute these funds through the welfare departments of all the counties in the state with the exception of Fulton County , which receives none of this money .\",\n",
       " \"The jurors said they realize `` a proportionate distribution of these funds might disable this program in our less populous counties '' .\",\n",
       " \"Nevertheless , `` we feel that in the future Fulton County should receive some portion of these available funds '' , the jurors said .\",\n",
       " \"`` Failure to do this will continue to place a disproportionate burden '' on Fulton taxpayers .\",\n",
       " \"The jury also commented on the Fulton ordinary's court which has been under fire for its practices in the appointment of appraisers , guardians and administrators and the awarding of fees and compensation .\",\n",
       " 'Wards protected',\n",
       " \"The jury said it found the court `` has incorporated into its operating procedures the recommendations '' of two previous grand juries , the Atlanta Bar Association and an interim citizens committee .\",\n",
       " \"`` These actions should serve to protect in fact and in effect the court's wards from undue costs and its appointed and elected servants from unmeritorious criticisms '' , the jury said .\",\n",
       " \"Regarding Atlanta's new multi-million-dollar airport , the jury recommended `` that when the new management takes charge Jan. 1 the airport be operated in a manner that will eliminate political influences '' .\",\n",
       " \"The jury did not elaborate , but it added that `` there should be periodic surveillance of the pricing practices of the concessionaires for the purpose of keeping the prices reasonable '' .\",\n",
       " 'Ask jail deputies',\n",
       " 'On other matters , the jury recommended that : ( 1 )',\n",
       " \"Four additional deputies be employed at the Fulton County Jail and `` a doctor , medical intern or extern be employed for night and weekend duty at the jail '' .\",\n",
       " '( 2 )',\n",
       " \"Fulton legislators `` work with city officials to pass enabling legislation that will permit the establishment of a fair and equitable '' pension plan for city employes .\",\n",
       " \"The jury praised the administration and operation of the Atlanta Police Department , the Fulton Tax Commissioner's Office , the Bellwood and Alpharetta prison farms , Grady Hospital and the Fulton Health Department .\",\n",
       " 'Mayor William B. Hartsfield filed suit for divorce from his wife , Pearl Williams Hartsfield , in Fulton Superior Court Friday .',\n",
       " 'His petition charged mental cruelty .',\n",
       " 'The couple was married Aug. 2 , 1913 .',\n",
       " 'They have a son , William Berry Jr. , and a daughter , Mrs. J. M. Cheshire of Griffin .',\n",
       " 'Attorneys for the mayor said that an amicable property settlement has been agreed upon .',\n",
       " \"The petition listed the mayor's occupation as `` attorney '' and his age as 71 .\",\n",
       " \"It listed his wife's age as 74 and place of birth as Opelika , Ala. .\",\n",
       " 'The petition said that the couple has not lived together as man and wife for more than a year .',\n",
       " 'The Hartsfield home is at 637 E. Pelham Rd. Aj .',\n",
       " \"Henry L. Bowden was listed on the petition as the mayor's attorney .\",\n",
       " 'Hartsfield has been mayor of Atlanta , with exception of one brief interlude , since 1937 .',\n",
       " 'His political career goes back to his election to city council in 1923 .',\n",
       " \"The mayor's present term of office expires Jan. 1 .\",\n",
       " 'He will be succeeded by Ivan Allen Jr. , who became a candidate in the Sept. 13 primary after Mayor Hartsfield announced that he would not run for reelection .',\n",
       " \"Georgia Republicans are getting strong encouragement to enter a candidate in the 1962 governor's race , a top official said Wednesday .\",\n",
       " 'Robert Snodgrass , state GOP chairman , said a meeting held Tuesday night in Blue Ridge brought enthusiastic responses from the audience .',\n",
       " 'State Party Chairman James W. Dorsey added that enthusiasm was picking up for a state rally to be held Sept. 8 in Savannah at which newly elected Texas Sen. John Tower will be the featured speaker .',\n",
       " 'In the Blue Ridge meeting , the audience was warned that entering a candidate for governor would force it to take petitions out into voting precincts to obtain the signatures of registered voters .',\n",
       " 'Despite the warning , there was a unanimous vote to enter a candidate , according to Republicans who attended .',\n",
       " 'When the crowd was asked whether it wanted to wait one more term to make the race , it voted no -- and there were no dissents .',\n",
       " 'The largest hurdle the Republicans would have to face is a state law which says that before making a first race , one of two alternative courses must be taken : 1',\n",
       " 'Five per cent of the voters in each county must sign petitions requesting that the Republicans be allowed to place names of candidates on the general election ballot , or 2',\n",
       " 'The Republicans must hold a primary under the county unit system -- a system which the party opposes in its platform .',\n",
       " \"Sam Caldwell , State Highway Department public relations director , resigned Tuesday to work for Lt. Gov. Garland Byrd's campaign .\",\n",
       " \"Caldwell's resignation had been expected for some time .\",\n",
       " 'He will be succeeded by Rob Ledford of Gainesville , who has been an assistant more than three years .',\n",
       " 'When the gubernatorial campaign starts , Caldwell is expected to become a campaign coordinator for Byrd .',\n",
       " 'The Georgia Legislature will wind up its 1961 session Monday and head for home -- where some of the highway bond money it approved will follow shortly .',\n",
       " 'Before adjournment Monday afternoon , the Senate is expected to approve a study of the number of legislators allotted to rural and urban areas to determine what adjustments should be made .',\n",
       " 'Gov. Vandiver is expected to make the traditional visit to both chambers as they work toward adjournment .',\n",
       " 'Vandiver likely will mention the $100 million highway bond issue approved earlier in the session as his first priority item .',\n",
       " 'Construction bonds',\n",
       " 'Meanwhile , it was learned the State Highway Department is very near being ready to issue the first $30 million worth of highway reconstruction bonds .',\n",
       " \"The bond issue will go to the state courts for a friendly test suit to test the validity of the act , and then the sales will begin and contracts let for repair work on some of Georgia's most heavily traveled highways .\",\n",
       " 'A Highway Department source said there also is a plan there to issue some $3 million to $4 million worth of Rural Roads Authority bonds for rural road construction work .',\n",
       " 'A revolving fund',\n",
       " 'The department apparently intends to make the Rural Roads Authority a revolving fund under which new bonds would be issued every time a portion of the old ones are paid off by tax authorities .',\n",
       " 'Vandiver opened his race for governor in 1958 with a battle in the Legislature against the issuance of $50 million worth of additional rural roads bonds proposed by then Gov. Marvin Griffin .',\n",
       " 'The Highway Department source told The Constitution , however , that Vandiver has not been consulted yet about the plans to issue the new rural roads bonds .',\n",
       " \"Schley County Rep. B. D. Pelham will offer a resolution Monday in the House to rescind the body's action of Friday in voting itself a $10 per day increase in expense allowances .\",\n",
       " \"Pelham said Sunday night there was research being done on whether the `` quickie '' vote on the increase can be repealed outright or whether notice would have to first be given that reconsideration of the action would be sought .\",\n",
       " 'While emphasizing that technical details were not fully worked out , Pelham said his resolution would seek to set aside the privilege resolution which the House voted through 87-31 .',\n",
       " 'A similar resolution passed in the Senate by a vote of 29-5 .',\n",
       " 'As of Sunday night , there was no word of a resolution being offered there to rescind the action .',\n",
       " 'Pelham pointed out that Georgia voters last November rejected a constitutional amendment to allow legislators to vote on pay raises for future Legislature sessions .',\n",
       " 'A veteran Jackson County legislator will ask the Georgia House Monday to back federal aid to education , something it has consistently opposed in the past .',\n",
       " \"Rep. Mac Barber of Commerce is asking the House in a privilege resolution to `` endorse increased federal support for public education , provided that such funds be received and expended '' as state funds .\",\n",
       " \"Barber , who is in his 13th year as a legislator , said there `` are some members of our congressional delegation in Washington who would like to see it ( the resolution ) passed '' .\",\n",
       " \"But he added that none of Georgia's congressmen specifically asked him to offer the resolution .\",\n",
       " 'The resolution , which Barber tossed into the House hopper Friday , will be formally read Monday .',\n",
       " \"It says that `` in the event Congress does provide this increase in federal funds '' , the State Board of Education should be directed to `` give priority '' to teacher pay raises .\",\n",
       " 'Colquitt',\n",
       " \"-- After a long , hot controversy , Miller County has a new school superintendent , elected , as a policeman put it , in the `` coolest election I ever saw in this county '' .\",\n",
       " 'The new school superintendent is Harry Davis , a veteran agriculture teacher , who defeated Felix Bush , a school principal and chairman of the Miller County Democratic Executive Committee .',\n",
       " \"Davis received 1,119 votes in Saturday's election , and Bush got 402 .\",\n",
       " 'Ordinary Carey Williams , armed with a pistol , stood by at the polls to insure order .',\n",
       " \"`` This was the coolest , calmest election I ever saw '' , Colquitt Policeman Tom Williams said .\",\n",
       " '`` Being at the polls was just like being at church .',\n",
       " \"I didn't smell a drop of liquor , and we didn't have a bit of trouble '' .\",\n",
       " 'The campaign leading to the election was not so quiet , however .',\n",
       " 'It was marked by controversy , anonymous midnight phone calls and veiled threats of violence .',\n",
       " 'The former county school superintendent , George P. Callan , shot himself to death March 18 , four days after he resigned his post in a dispute with the county school board .',\n",
       " 'During the election campaign , both candidates , Davis and Bush , reportedly received anonymous telephone calls .',\n",
       " 'Ordinary Williams said he , too , was subjected to anonymous calls soon after he scheduled the election .',\n",
       " 'Many local citizens feared that there would be irregularities at the polls , and Williams got himself a permit to carry a gun and promised an orderly election .',\n",
       " 'Sheriff Felix Tabb said the ordinary apparently made good his promise .',\n",
       " \"`` Everything went real smooth '' , the sheriff said .\",\n",
       " \"`` There wasn't a bit of trouble '' .\"]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[' '.join(sent) for sent in sentences]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TextCleaner():\n",
    "    \n",
    "    def __init__(self):\n",
    "        self.stop_words = set(stopwords.words(\"english\"))\n",
    "        self.punctuations = set(string.punctuation)\n",
    "        self.pos_tags = {\n",
    "                NOUN: ['NN', 'NNS', 'NNP', 'NNPS', 'PRP', 'PRP$', 'WP', 'WP$'],\n",
    "                VERB: ['VB', 'VBD', 'VBG', 'VBN', 'VBP', 'VBZ'],\n",
    "                ADJ: ['JJ', 'JJR', 'JJS'],\n",
    "                ADV: ['RB', 'RBR', 'RBS', 'WRB']\n",
    "        }\n",
    "\n",
    "\n",
    "    def _remove_stop_words(self, words):\n",
    "        return [w for w in words if w not in self.stop_words]\n",
    "     \n",
    "    \n",
    "    def _remove_regex(self):\n",
    "        self.input_sent = \" \".join([w.lower() for w in self.input_sent])\n",
    "        self.input_sent = re.sub(r\"i'm\", \"i am\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"he's\", \"he is\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"she's\", \"she is\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"that's\", \"that is\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"what's\", \"what is\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"where's\", \"where is\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"\\'ll\", \" will\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"\\'ve\", \" have\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"\\'re\", \" are\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"\\'d\", \" would\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"won't\", \"will not\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"can't\", \"cannot\", self.input_sent)\n",
    "        self.input_sent = re.sub(r\"don't\", \"do not\", self.input_sent)\n",
    "        patterns = re.finditer(\"#[\\w]*\", self.input_sent)\n",
    "        for pattern in patterns:\n",
    "            self.input_sent = re.sub(pattern.group().strip(), \"\", self.input_sent)\n",
    "        self.input_sent = \"\".join(ch for ch in self.input_sent if ch not in self.punctuations)\n",
    "    \n",
    "    \n",
    "    def _tokenize(self):\n",
    "        return word_tokenize(self.input_sent)\n",
    "    \n",
    "    \n",
    "    def _process_content_for_pos(self, words):\n",
    "        tagged_words = pos_tag(words)\n",
    "        pos_words = []\n",
    "        for word in tagged_words:\n",
    "            flag = False\n",
    "            for key, value in self.pos_tags.items():\n",
    "                if word[1] in value:\n",
    "                    pos_words.append((word[0], key))\n",
    "                    flag = True\n",
    "                    break\n",
    "            if not flag:\n",
    "                pos_words.append((word[0], NOUN))\n",
    "        return pos_words\n",
    "       \n",
    "                 \n",
    "    def _remove_noise(self):\n",
    "        self._remove_regex()\n",
    "        words = self._tokenize()\n",
    "        noise_free_words = self._remove_stop_words(words)\n",
    "        return noise_free_words\n",
    "    \n",
    "    \n",
    "    def _normalize_text(self, words):\n",
    "        lem = WordNetLemmatizer()\n",
    "        pos_words = self._process_content_for_pos(words)\n",
    "        normalized_words = [lem.lemmatize(w, pos=p) for w, p in pos_words]\n",
    "        return normalized_words\n",
    "    \n",
    "    \n",
    "    def clean_up(self, input_sent):\n",
    "        self.input_sent = input_sent\n",
    "        cleaned_words = self._remove_noise()\n",
    "        cleaned_words = self._normalize_text(cleaned_words)\n",
    "        return cleaned_words"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## PageRank Algorithm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def pagerank(M, eps=1.0e-8, d=0.85):\n",
    "    N = M.shape[1]\n",
    "    v = np.random.rand(N, 1)\n",
    "    v = v / np.linalg.norm(v, 1)\n",
    "    last_v = np.ones((N, 1), dtype=np.float32) * np.inf\n",
    "    M_hat = (d * M) + (((1 - d) / N) * np.ones((N, N), dtype=np.float32))\n",
    "    \n",
    "    while np.linalg.norm(v - last_v, 2) > eps:\n",
    "        last_v = v\n",
    "        v = np.matmul(M_hat, v)\n",
    "    return v"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Function to calculate cosine similarity among sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "def sentence_similarity(sent1, sent2):\n",
    "    text_cleaner = TextCleaner()\n",
    "    \n",
    "    sent1 = text_cleaner.clean_up(sent1)\n",
    "    sent2 = text_cleaner.clean_up(sent2)\n",
    "    \n",
    "    all_words = list(set(sent1 + sent2))\n",
    "    \n",
    "    vector1 = [0] * len(all_words)\n",
    "    vector2 = [0] * len(all_words)\n",
    "    \n",
    "    for w in sent1:\n",
    "        vector1[all_words.index(w)] += 1\n",
    "    \n",
    "    for w in sent2:\n",
    "        vector2[all_words.index(w)] += 1\n",
    "    \n",
    "    return 1 - cosine_distance(vector1, vector2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Similarity Adjacency Matrix for PageRank"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def build_similarity_matrix(sentences):\n",
    "    S = np.zeros((len(sentences), len(sentences)))\n",
    "    for i in range(len(sentences)):\n",
    "        for j in range(len(sentences)):\n",
    "            if i == j:\n",
    "                continue\n",
    "            else:\n",
    "                S[i][j] = sentence_similarity(sentences[i], sentences[j])\n",
    "    \n",
    "    for i in range(len(S)):\n",
    "        S[i] /= S[i].sum()\n",
    "    return S"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "S = build_similarity_matrix(sentences)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.        , 0.03809933, 0.03196713, ..., 0.01191345, 0.01459093,\n",
       "        0.        ],\n",
       "       [0.04793482, 0.        , 0.01714968, ..., 0.01278262, 0.01565545,\n",
       "        0.        ],\n",
       "       [0.07569435, 0.03227618, 0.        , ..., 0.        , 0.        ,\n",
       "        0.        ],\n",
       "       ...,\n",
       "       [0.02576081, 0.02196889, 0.        , ..., 0.        , 0.08413444,\n",
       "        0.        ],\n",
       "       [0.03354197, 0.02860469, 0.        , ..., 0.08944524, 0.        ,\n",
       "        0.        ],\n",
       "       [0.        , 0.        , 0.        , ..., 0.        , 0.        ,\n",
       "        0.        ]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "S"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "sentence_ranks = pagerank(S)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Sentence Ranked according to their importance**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[0.01921274],\n",
       "       [0.00901109],\n",
       "       [0.00350104],\n",
       "       [0.00771284],\n",
       "       [0.00682507],\n",
       "       [0.00228502],\n",
       "       [0.00398724],\n",
       "       [0.01132934],\n",
       "       [0.01635211],\n",
       "       [0.01792972],\n",
       "       [0.01527026],\n",
       "       [0.01670458],\n",
       "       [0.01725918],\n",
       "       [0.01287142],\n",
       "       [0.00509116],\n",
       "       [0.00400374],\n",
       "       [0.00206901],\n",
       "       [0.01854068],\n",
       "       [0.01125827],\n",
       "       [0.00730178],\n",
       "       [0.00650502],\n",
       "       [0.01893981],\n",
       "       [0.01734668],\n",
       "       [0.00196538],\n",
       "       [0.01251376],\n",
       "       [0.00764603],\n",
       "       [0.01150424],\n",
       "       [0.00118629],\n",
       "       [0.00430547],\n",
       "       [0.01311848],\n",
       "       [0.01149023],\n",
       "       [0.02008372],\n",
       "       [0.02003183],\n",
       "       [0.01349925],\n",
       "       [0.00782215],\n",
       "       [0.00277988],\n",
       "       [0.01910414],\n",
       "       [0.00831641],\n",
       "       [0.01396597],\n",
       "       [0.01464962],\n",
       "       [0.00389179],\n",
       "       [0.01058644],\n",
       "       [0.01526401],\n",
       "       [0.00914281],\n",
       "       [0.01543596],\n",
       "       [0.00246883],\n",
       "       [0.01528529],\n",
       "       [0.00194479],\n",
       "       [0.00457946],\n",
       "       [0.01298577],\n",
       "       [0.00735999],\n",
       "       [0.01589343],\n",
       "       [0.00114008],\n",
       "       [0.00433111],\n",
       "       [0.00527591],\n",
       "       [0.00322515],\n",
       "       [0.00130911],\n",
       "       [0.00477306],\n",
       "       [0.01532199],\n",
       "       [0.01368336],\n",
       "       [0.01652476],\n",
       "       [0.00689699],\n",
       "       [0.011595  ],\n",
       "       [0.00734665],\n",
       "       [0.01478425],\n",
       "       [0.01076639],\n",
       "       [0.00083697],\n",
       "       [0.01969609],\n",
       "       [0.01051274],\n",
       "       [0.01672018],\n",
       "       [0.0064825 ],\n",
       "       [0.00658627],\n",
       "       [0.00188099],\n",
       "       [0.0133002 ],\n",
       "       [0.0056044 ],\n",
       "       [0.00044107],\n",
       "       [0.01444426],\n",
       "       [0.00491386],\n",
       "       [0.00519114],\n",
       "       [0.01259626],\n",
       "       [0.01659438],\n",
       "       [0.01609447],\n",
       "       [0.01860189],\n",
       "       [0.00264916],\n",
       "       [0.00583905],\n",
       "       [0.00706126],\n",
       "       [0.01521225],\n",
       "       [0.00881925],\n",
       "       [0.01427717],\n",
       "       [0.00834345],\n",
       "       [0.01710864],\n",
       "       [0.01335878],\n",
       "       [0.01689836],\n",
       "       [0.00176757],\n",
       "       [0.0100603 ],\n",
       "       [0.01334393],\n",
       "       [0.01866685],\n",
       "       [0.00899336]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sentence_ranks"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "ranked_sentence_indexes = [item[0] for item in sorted(enumerate(sentence_ranks), key=lambda item: -item[1])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[31,\n",
       " 32,\n",
       " 67,\n",
       " 0,\n",
       " 36,\n",
       " 21,\n",
       " 96,\n",
       " 82,\n",
       " 17,\n",
       " 9,\n",
       " 22,\n",
       " 12,\n",
       " 90,\n",
       " 92,\n",
       " 69,\n",
       " 11,\n",
       " 80,\n",
       " 60,\n",
       " 8,\n",
       " 81,\n",
       " 51,\n",
       " 44,\n",
       " 58,\n",
       " 46,\n",
       " 10,\n",
       " 42,\n",
       " 86,\n",
       " 64,\n",
       " 39,\n",
       " 76,\n",
       " 88,\n",
       " 38,\n",
       " 59,\n",
       " 33,\n",
       " 91,\n",
       " 95,\n",
       " 73,\n",
       " 29,\n",
       " 49,\n",
       " 13,\n",
       " 79,\n",
       " 24,\n",
       " 62,\n",
       " 26,\n",
       " 30,\n",
       " 7,\n",
       " 18,\n",
       " 65,\n",
       " 41,\n",
       " 68,\n",
       " 94,\n",
       " 43,\n",
       " 1,\n",
       " 97,\n",
       " 87,\n",
       " 89,\n",
       " 37,\n",
       " 34,\n",
       " 3,\n",
       " 25,\n",
       " 50,\n",
       " 63,\n",
       " 19,\n",
       " 85,\n",
       " 61,\n",
       " 4,\n",
       " 71,\n",
       " 20,\n",
       " 70,\n",
       " 84,\n",
       " 74,\n",
       " 54,\n",
       " 78,\n",
       " 14,\n",
       " 77,\n",
       " 57,\n",
       " 48,\n",
       " 53,\n",
       " 28,\n",
       " 15,\n",
       " 6,\n",
       " 40,\n",
       " 2,\n",
       " 55,\n",
       " 35,\n",
       " 83,\n",
       " 45,\n",
       " 5,\n",
       " 16,\n",
       " 23,\n",
       " 47,\n",
       " 72,\n",
       " 93,\n",
       " 56,\n",
       " 27,\n",
       " 52,\n",
       " 66,\n",
       " 75]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranked_sentence_indexes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1f2a25f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.bar([item[0] for item in sorted(enumerate(sentence_ranks))], sentence_ranks.T[0])\n",
    "plt.xlabel(\"Sentence No.\")\n",
    "plt.ylabel(\"Importance\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1a1f2a2710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([item[0] for item in sorted(enumerate(sentence_ranks))], sentence_ranks)\n",
    "plt.xlabel(\"Sentence No.\")\n",
    "plt.ylabel(\"Importance\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "SUMMARY_SIZE = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_sentences = sorted(ranked_sentence_indexes[:SUMMARY_SIZE])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0, 31, 32, 36, 67]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "selected_sentences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "summary = itemgetter(*selected_sentences)(sentences)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Generated Summary**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Fulton County Grand Jury said Friday an investigation of Atlanta's recent primary election produced `` no evidence '' that any irregularities took place .\n",
      "His petition charged mental cruelty .\n",
      "The couple was married Aug. 2 , 1913 .\n",
      "It listed his wife's age as 74 and place of birth as Opelika , Ala. .\n",
      "Vandiver opened his race for governor in 1958 with a battle in the Legislature against the issuance of $50 million worth of additional rural roads bonds proposed by then Gov. Marvin Griffin .\n"
     ]
    }
   ],
   "source": [
    "for sent in summary:\n",
    "    print(' '.join(sent))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}