semantc_text_segmentation_example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Semantically Segmenting Text Using Word Embeddings and Greedy Sequence Segmentation\n",
    "\n",
    "This notebook illustrates how to use the text_segmentation_class in text_segmetnation.py to semantically segment a text document.The class converts a document's words into GloVe embeddings and uses the embedding information to semantically segment the document into k segmetns, where k is given.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import spacy\n",
    "import nltk\n",
    "import os\n",
    "from gensim.models import KeyedVectors\n",
    "import numpy as np\n",
    "from nltk.corpus import stopwords\n",
    "from sklearn.feature_extraction.text import TfidfVectorizer\n",
    "import string\n",
    "import math\n",
    "from scipy import spatial\n",
    "import matplotlib.pyplot as plt\n",
    "import mpld3\n",
    "\n",
    "import text_segmentation as ts\n",
    "\n",
    "# For interactive plots within the python notebook\n",
    "mpld3.enable_notebook()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# the directory containing the Stanford GloVe model\n",
    "# Change this to the proper path in your environment\n",
    "glove_file = '/media/datadr/embeddings/glove.6B.100d.txt.word2vec'\n",
    "\n",
    "# the document to be segmented\n",
    "file_name=\"sample.txt\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Chemical reaction, a process in which one or more substances, the reactants, are converted to one or more different substances, the products. Substances are either chemical elements or compounds. A chemical reaction rearranges the constituent atoms of the reactants to create different substances as products.\n",
      "\n",
      "Chemical reactions are an integral part of technology, of culture, and indeed of life itself. Burning fuels, smelting iron, making glass and pottery, brewing beer, and making wine and cheese are among many examples of activities incorporating chemical reactions that have been known and used for thousands of years. Chemical reactions abound in the geology of Earth, in the atmosphere and oceans, and in a vast array of complicated processes that occur in all living systems.\n",
      "\n",
      "Chemical reactions must be distinguished from physical changes. Physical changes include changes of state, such as ice melting to water and water evaporating to vapour. If a physical change occurs, the physical properties of a substance will change, but its chemical identity will remain the same. No matter what its physical state, water (H2O) is the same compound, with each molecule composed of two atoms of hydrogen and one atom of oxygen. However, if water, as ice, liquid, or vapour, encounters sodium metal (Na), the atoms will be redistributed to give the new substances molecular hydrogen (H2) and sodium hydroxide (NaOH). By this, we know that a chemical change or reaction has occurred.\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Instantiating the text segmetnation class object\n",
    "seg_obj = ts.text_segmentation_class(file_name, glove_file)\n",
    "\n",
    "#seg_boj.doc contains the text of the document to be segmented\n",
    "print(seg_obj.doc)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Find best segmentation boundaries to create n segments, for a given k\n",
    "k=3\n",
    "\n",
    "# Segment text into k segments using the greedy method\n",
    "seg_obj.greedy_text_segmentation(k);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/html": [
       "\n",
       "\n",
       "<style>\n",
       "\n",
       "</style>\n",
       "\n",
       "<div id=\"fig_el54581405581436958407452589354\"></div>\n",
       "<script>\n",
       "function mpld3_load_lib(url, callback){\n",
       "  var s = document.createElement('script');\n",
       "  s.src = url;\n",
       "  s.async = true;\n",
       "  s.onreadystatechange = s.onload = callback;\n",
       "  s.onerror = function(){console.warn(\"failed to load library \" + url);};\n",
       "  document.getElementsByTagName(\"head\")[0].appendChild(s);\n",
       "}\n",
       "\n",
       "if(typeof(mpld3) !== \"undefined\" && mpld3._mpld3IsLoaded){\n",
       "   // already loaded: just create the figure\n",
       "   !function(mpld3){\n",
       "       \n",
       "       mpld3.draw_figure(\"fig_el54581405581436958407452589354\", {\"id\": \"el5458140558143695840\", \"plugins\": [{\"type\": \"reset\"}, {\"enabled\": false, \"button\": true, \"type\": \"zoom\"}, {\"enabled\": false, \"button\": true, \"type\": \"boxzoom\"}], \"width\": 432.0, \"axes\": [{\"paths\": [], \"images\": [], \"xdomain\": [-7.0, 147.0], \"texts\": [{\"position\": [0.49999999999999994, -0.09657836644591611], \"h_anchor\": \"middle\", \"alpha\": 1, \"coordinates\": \"axes\", \"zorder\": 3, \"text\": \"word position\", \"id\": \"el5458140558143741344\", \"color\": \"#000000\", \"rotation\": -0.0, \"v_baseline\": \"hanging\", \"fontsize\": 10.0}, {\"position\": [-0.11835424133811231, 0.49999999999999994], \"h_anchor\": \"middle\", \"alpha\": 1, \"coordinates\": \"axes\", \"zorder\": 3, \"text\": \"Homogeniouty (higher is better)\", \"id\": \"el5458140558143812048\", \"color\": \"#000000\", \"rotation\": -90.0, \"v_baseline\": \"auto\", \"fontsize\": 10.0}, {\"position\": [0.49999999999999994, 1.0275938189845473], \"h_anchor\": \"middle\", \"alpha\": 1, \"coordinates\": \"axes\", \"zorder\": 3, \"text\": \"Homogeniouty of segment from first word to 'word position' \", \"id\": \"el5458140558109823552\", \"color\": \"#000000\", \"rotation\": -0.0, \"v_baseline\": \"auto\", \"fontsize\": 12.0}], \"axes\": [{\"scale\": \"linear\", \"tickformat\": null, \"position\": \"bottom\", \"nticks\": 10, \"grid\": {\"gridOn\": false}, \"tickvalues\": null, \"fontsize\": 10.0, \"visible\": true}, {\"scale\": \"linear\", \"tickformat\": null, \"position\": \"left\", \"nticks\": 8, \"grid\": {\"gridOn\": false}, \"tickvalues\": null, \"fontsize\": 10.0, \"visible\": true}], \"axesbgalpha\": null, \"collections\": [], \"xlim\": [-7.0, 147.0], \"bbox\": [0.125, 0.125, 0.775, 0.755], \"yscale\": \"linear\", \"lines\": [{\"xindex\": 0, \"dasharray\": \"none\", \"id\": \"el5458140558109862824\", \"color\": \"#1F77B4\", \"drawstyle\": \"default\", \"alpha\": 1, \"linewidth\": 1.5, \"coordinates\": \"data\", \"yindex\": 1, \"zorder\": 2, \"data\": \"data01\"}, {\"xindex\": 0, \"dasharray\": \"none\", \"id\": \"el5458140558109823832\", \"color\": \"#FF7F0E\", \"drawstyle\": \"default\", \"alpha\": 1, \"linewidth\": 1.5, \"coordinates\": \"data\", \"yindex\": 2, \"zorder\": 2, \"data\": \"data01\"}, {\"xindex\": 0, \"dasharray\": \"none\", \"id\": \"el5458140558109914504\", \"color\": \"#2CA02C\", \"drawstyle\": \"default\", \"alpha\": 1, \"linewidth\": 1.5, \"coordinates\": \"data\", \"yindex\": 3, \"zorder\": 2, \"data\": \"data01\"}], \"ylim\": [0.9744816151448206, 1.00121516118358], \"sharey\": [], \"xscale\": \"linear\", \"markers\": [], \"id\": \"el5458140558143738768\", \"zoomable\": true, \"axesbg\": \"#FFFFFF\", \"sharex\": [], \"ydomain\": [0.9744816151448206, 1.00121516118358]}], \"height\": 288.0, \"data\": {\"data01\": [[0.0, 0.9999999790632828, 1.0, 1.0], [1.0, 0.9890531819275898, 1.0, 1.0], [2.0, 0.9878522390509161, 1.0, 1.0], [3.0, 0.9835770513024864, 1.0, 1.0], [4.0, 0.9809021704032057, 1.0, 1.0], [5.0, 0.9785181347671225, 1.0, 1.0], [6.0, 0.978363830479106, 1.0, 1.0], [7.0, 0.9776390717846395, 1.0, 1.0], [8.0, 0.9782092878852472, 1.0, 1.0], [9.0, 0.977960759653149, 1.0, 1.0], [10.0, 0.9783931134956717, 1.0, 1.0], [11.0, 0.9786848933514991, 1.0, 1.0], [12.0, 0.9793012639070657, 1.0, 1.0], [13.0, 0.979242215353787, 1.0, 1.0], [14.0, 0.9797317282608884, 1.0, 1.0], [15.0, 0.9803870905102373, 1.0, 1.0], [16.0, 0.9805990287685027, 1.0, 1.0], [17.0, 0.9807890791384131, 1.0, 1.0], [18.0, 0.9802946754022265, 1.0, 1.0], [19.0, 0.9793288317728887, 1.0, 1.0], [20.0, 0.9791592669948271, 1.0, 1.0], [21.0, 0.9783928246617479, 1.0, 1.0], [22.0, 0.9778501708750837, 1.0, 1.0], [23.0, 0.9781201811047003, 1.0, 1.0], [24.0, 0.9781575159825909, 1.0, 0.9895267765259829], [25.0, 0.9780818348473299, 1.0, 0.9850811198392564], [26.0, 0.9781978571009556, 1.0, 0.9841144488032483], [27.0, 0.9783662928481758, 1.0, 0.9838743706472226], [28.0, 0.9779592673624806, 1.0, 0.9809890678331881], [29.0, 0.9779678794498288, 1.0, 0.9805931481402934], [30.0, 0.9781102038712257, 1.0, 0.9808164966868986], [31.0, 0.9782980761227252, 1.0, 0.9811837877127109], [32.0, 0.9783225616585107, 1.0, 0.9809760188218044], [33.0, 0.9784749293038841, 1.0, 0.9812057499835685], [34.0, 0.9785758382396991, 1.0, 0.9812724993230548], [35.0, 0.9786187835315452, 1.0, 0.9811839892786783], [36.0, 0.9787018385909599, 1.0, 0.9812202629537647], [37.0, 0.9786044309958993, 1.0, 0.9808056020887578], [38.0, 0.9786965799918675, 1.0, 0.9808926420731268], [39.0, 0.9786132585305726, 1.0, 0.9805674114535349], [40.0, 0.9786678537878305, 1.0, 0.9805832032660133], [41.0, 0.9785699941222896, 1.0, 0.9802660740328082], [42.0, 0.9784692104055472, 1.0, 0.9799645850462861], [43.0, 0.9784714003740363, 1.0, 0.9798979652354661], [44.0, 0.9784348753543756, 1.0, 0.9797584111106404], [45.0, 0.9784431961877981, 1.0, 0.9797175077446045], [46.0, 0.9783655450199875, 1.0, 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       "   }(mpld3);\n",
       "}else if(typeof define === \"function\" && define.amd){\n",
       "   // require.js is available: use it to load d3/mpld3\n",
       "   require.config({paths: {d3: \"https://mpld3.github.io/js/d3.v3.min\"}});\n",
       "   require([\"d3\"], function(d3){\n",
       "      window.d3 = d3;\n",
       "      mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.3.js\", function(){\n",
       "         \n",
       "         mpld3.draw_figure(\"fig_el54581405581436958407452589354\", {\"id\": \"el5458140558143695840\", \"plugins\": [{\"type\": \"reset\"}, {\"enabled\": false, \"button\": true, \"type\": \"zoom\"}, {\"enabled\": false, \"button\": true, \"type\": \"boxzoom\"}], \"width\": 432.0, \"axes\": [{\"paths\": [], \"images\": [], \"xdomain\": [-7.0, 147.0], \"texts\": [{\"position\": [0.49999999999999994, -0.09657836644591611], \"h_anchor\": \"middle\", \"alpha\": 1, \"coordinates\": \"axes\", \"zorder\": 3, \"text\": \"word position\", \"id\": \"el5458140558143741344\", \"color\": \"#000000\", \"rotation\": -0.0, \"v_baseline\": \"hanging\", \"fontsize\": 10.0}, {\"position\": [-0.11835424133811231, 0.49999999999999994], \"h_anchor\": \"middle\", \"alpha\": 1, \"coordinates\": \"axes\", \"zorder\": 3, \"text\": \"Homogeniouty (higher is better)\", \"id\": \"el5458140558143812048\", \"color\": \"#000000\", \"rotation\": -90.0, \"v_baseline\": \"auto\", \"fontsize\": 10.0}, {\"position\": [0.49999999999999994, 1.0275938189845473], \"h_anchor\": \"middle\", \"alpha\": 1, \"coordinates\": \"axes\", \"zorder\": 3, \"text\": \"Homogeniouty of segment from first word to 'word position' \", \"id\": \"el5458140558109823552\", \"color\": \"#000000\", \"rotation\": -0.0, \"v_baseline\": \"auto\", \"fontsize\": 12.0}], \"axes\": [{\"scale\": \"linear\", \"tickformat\": null, \"position\": \"bottom\", \"nticks\": 10, \"grid\": {\"gridOn\": false}, \"tickvalues\": null, \"fontsize\": 10.0, \"visible\": true}, {\"scale\": \"linear\", \"tickformat\": null, \"position\": \"left\", \"nticks\": 8, \"grid\": {\"gridOn\": false}, \"tickvalues\": null, \"fontsize\": 10.0, \"visible\": true}], \"axesbgalpha\": null, \"collections\": [], \"xlim\": [-7.0, 147.0], \"bbox\": [0.125, 0.125, 0.775, 0.755], \"yscale\": \"linear\", \"lines\": [{\"xindex\": 0, \"dasharray\": \"none\", \"id\": \"el5458140558109862824\", \"color\": \"#1F77B4\", \"drawstyle\": \"default\", \"alpha\": 1, \"linewidth\": 1.5, \"coordinates\": \"data\", \"yindex\": 1, \"zorder\": 2, \"data\": \"data01\"}, {\"xindex\": 0, \"dasharray\": \"none\", \"id\": \"el5458140558109823832\", \"color\": \"#FF7F0E\", \"drawstyle\": \"default\", \"alpha\": 1, \"linewidth\": 1.5, \"coordinates\": \"data\", \"yindex\": 2, \"zorder\": 2, \"data\": \"data01\"}, {\"xindex\": 0, \"dasharray\": \"none\", \"id\": \"el5458140558109914504\", \"color\": \"#2CA02C\", \"drawstyle\": \"default\", \"alpha\": 1, \"linewidth\": 1.5, \"coordinates\": \"data\", \"yindex\": 3, \"zorder\": 2, \"data\": \"data01\"}], \"ylim\": [0.9744816151448206, 1.00121516118358], \"sharey\": [], \"xscale\": \"linear\", \"markers\": [], \"id\": \"el5458140558143738768\", \"zoomable\": true, \"axesbg\": \"#FFFFFF\", \"sharex\": [], \"ydomain\": [0.9744816151448206, 1.00121516118358]}], \"height\": 288.0, \"data\": {\"data01\": [[0.0, 0.9999999790632828, 1.0, 1.0], [1.0, 0.9890531819275898, 1.0, 1.0], [2.0, 0.9878522390509161, 1.0, 1.0], 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0.9774019299684262], [92.0, 0.9774167464788927, 0.9761927749588959, 0.9774981868003458], [93.0, 0.9772645265645373, 0.9758953954036822, 0.9772955091627281], [94.0, 0.9773600523686347, 0.9761274861270178, 0.9774211198403817], [95.0, 0.9774859547844348, 0.9764170339130707, 0.9775858535999031], [96.0, 0.9774597976376705, 0.9763857930116928, 0.9775502165451518], [97.0, 0.9774188174806827, 0.9763245002875505, 0.9774954635545879], [98.0, 0.9774485234134231, 0.9764068514004981, 0.9775331509396853], [99.0, 0.9774983389081692, 0.9765273158302487, 0.9775967473286248], [100.0, 0.9776011279526329, 0.9767499181159104, 0.9777285843167065], [101.0, 0.9777006262386732, 0.9769614572507727, 0.9778554370864792], [102.0, 0.9775747953030851, 0.976730864470062, 0.977691494621312], [103.0, 0.9775175942559852, 0.9766363278392216, 0.9776166105692549], [104.0, 0.977398485322623, 0.9764249610831076, 0.9774628855166171], [105.0, 0.9773423853844478, 0.976336156275839, 0.97739046390649], [106.0, 0.9774009288199883, 0.9764637067444608, 0.9774644647288803], [107.0, 0.9774351421799126, 0.976543573381484, 0.9775071883402089], [108.0, 0.9774452939575086, 0.976577439695999, 0.9775192173820421], [109.0, 0.9775226835568285, 0.9767337848657774, 0.9776162166061876], [110.0, 0.977337313497336, 0.976409404899997, 0.9773813346783123], [111.0, 0.9773003806843776, 0.9763576538281583, 0.9773343628105337], [112.0, 0.9772542602827466, 0.9762898938515219, 0.9772760785048618], [113.0, 0.9772825354805358, 0.9763553272730717, 0.9773112604205305], [114.0, 0.9773516812949635, 0.9764919269171741, 0.9773973804609565], [115.0, 0.9774471826640723, 0.9766728043898166, 0.9775160090593503], [116.0, 0.9773562819160757, 0.9765256251474085, 0.9774021344432772], [117.0, 0.977308416235071, 0.9764547796534396, 0.9773421975707955], [118.0, 0.9773928973350675, 0.9766128504865007, 0.977446567045419], [119.0, 0.9772309392622882, 0.97634635160243, 0.9772456532470286], [120.0, 0.9772194156146111, 0.9763391716910346, 0.9772312749270932], [121.0, 0.977115888696387, 0.9761759766896491, 0.9771035765095597], [122.0, 0.9771737133194913, 0.9762862827259307, 0.9771748239178462], [123.0, 0.9771001798557258, 0.9761750567946692, 0.9770845342138337], [124.0, 0.9769599211403509, 0.9759536272431917, 0.9769128019218731], [125.0, 0.9768836886768079, 0.9758404825522803, 0.9768200041433494], [126.0, 0.9769444930846042, 0.9759543184732499, 0.9768948680310762], [127.0, 0.9770121564879133, 0.9760780503993387, 0.9769778255613343], [128.0, 0.9769012451182848, 0.9759087660880286, 0.9768431723938296], [129.0, 0.97696241886113, 0.9760205794080301, 0.976918038368543], [130.0, 0.9769496330510423, 0.9760115287701489, 0.976902940584942], [131.0, 0.9769063689641493, 0.9759533244385759, 0.976850975750045], [132.0, 0.9768246148523472, 0.9758338033259961, 0.9767526311713578], [133.0, 0.9768226769975649, 0.9758425073615382, 0.9767509402807287], [134.0, 0.9767236599053225, 0.9756967763284006, 0.9766322298277297], [135.0, 0.9767843034754935, 0.9758046182949143, 0.9767060258951709], [136.0, 0.9768350987980051, 0.9758958670807151, 0.9767677560422271], [137.0, 0.976791281011006, 0.9758378259115265, 0.9767157602870088], [138.0, 0.9767683296985374, 0.975812693581935, 0.9766889093239991], [139.0, 0.9767461319283642, 0.9757887818962945, 0.9766630266962237], [140.0, 0.9767796679868049, 0.9758512646904945, 0.9767038037256499]]}});\n",
       "      });\n",
       "    });\n",
       "}else{\n",
       "    // require.js not available: dynamically load d3 & mpld3\n",
       "    mpld3_load_lib(\"https://mpld3.github.io/js/d3.v3.min.js\", function(){\n",
       "         mpld3_load_lib(\"https://mpld3.github.io/js/mpld3.v0.3.js\", function(){\n",
       "                 \n",
       "                 mpld3.draw_figure(\"fig_el54581405581436958407452589354\", {\"id\": \"el5458140558143695840\", \"plugins\": [{\"type\": \"reset\"}, {\"enabled\": false, \"button\": true, \"type\": \"zoom\"}, {\"enabled\": false, \"button\": true, \"type\": \"boxzoom\"}], \"width\": 432.0, \"axes\": [{\"paths\": [], \"images\": [], \"xdomain\": [-7.0, 147.0], \"texts\": [{\"position\": [0.49999999999999994, -0.09657836644591611], \"h_anchor\": \"middle\", \"alpha\": 1, \"coordinates\": \"axes\", \"zorder\": 3, \"text\": \"word position\", \"id\": \"el5458140558143741344\", \"color\": \"#000000\", \"rotation\": -0.0, \"v_baseline\": \"hanging\", \"fontsize\": 10.0}, {\"position\": [-0.11835424133811231, 0.49999999999999994], \"h_anchor\": \"middle\", \"alpha\": 1, \"coordinates\": \"axes\", \"zorder\": 3, \"text\": \"Homogeniouty (higher is better)\", \"id\": \"el5458140558143812048\", \"color\": \"#000000\", \"rotation\": -90.0, \"v_baseline\": \"auto\", \"fontsize\": 10.0}, {\"position\": [0.49999999999999994, 1.0275938189845473], \"h_anchor\": \"middle\", \"alpha\": 1, \"coordinates\": \"axes\", \"zorder\": 3, \"text\": \"Homogeniouty of segment from first word to 'word position' \", \"id\": \"el5458140558109823552\", \"color\": \"#000000\", \"rotation\": -0.0, \"v_baseline\": \"auto\", \"fontsize\": 12.0}], \"axes\": [{\"scale\": \"linear\", \"tickformat\": null, \"position\": \"bottom\", \"nticks\": 10, \"grid\": {\"gridOn\": false}, \"tickvalues\": null, \"fontsize\": 10.0, \"visible\": true}, {\"scale\": \"linear\", \"tickformat\": null, \"position\": \"left\", \"nticks\": 8, \"grid\": {\"gridOn\": false}, \"tickvalues\": null, \"fontsize\": 10.0, \"visible\": true}], \"axesbgalpha\": null, \"collections\": [], \"xlim\": [-7.0, 147.0], \"bbox\": [0.125, 0.125, 0.775, 0.755], \"yscale\": \"linear\", \"lines\": [{\"xindex\": 0, \"dasharray\": \"none\", \"id\": \"el5458140558109862824\", \"color\": \"#1F77B4\", \"drawstyle\": \"default\", \"alpha\": 1, \"linewidth\": 1.5, \"coordinates\": \"data\", \"yindex\": 1, \"zorder\": 2, \"data\": \"data01\"}, {\"xindex\": 0, \"dasharray\": \"none\", \"id\": \"el5458140558109823832\", \"color\": \"#FF7F0E\", \"drawstyle\": \"default\", \"alpha\": 1, \"linewidth\": 1.5, \"coordinates\": \"data\", \"yindex\": 2, \"zorder\": 2, \"data\": \"data01\"}, {\"xindex\": 0, \"dasharray\": \"none\", \"id\": \"el5458140558109914504\", \"color\": \"#2CA02C\", \"drawstyle\": \"default\", \"alpha\": 1, \"linewidth\": 1.5, \"coordinates\": \"data\", \"yindex\": 3, \"zorder\": 2, \"data\": \"data01\"}], \"ylim\": [0.9744816151448206, 1.00121516118358], \"sharey\": [], \"xscale\": \"linear\", \"markers\": [], \"id\": \"el5458140558143738768\", \"zoomable\": true, \"axesbg\": \"#FFFFFF\", \"sharex\": [], \"ydomain\": [0.9744816151448206, 1.00121516118358]}], \"height\": 288.0, \"data\": {\"data01\": [[0.0, 0.9999999790632828, 1.0, 1.0], [1.0, 0.9890531819275898, 1.0, 1.0], [2.0, 0.9878522390509161, 1.0, 1.0], 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       "            })\n",
       "         });\n",
       "}\n",
       "</script>"
      ],
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# type\n",
    "# for each segment S from a word i to another word j in the document, \n",
    "# we measure D the average distance of each word in the segment from the segment's centroid\n",
    "# The smaller that distance, the more homogeneneous the segment\n",
    "# therefor, homogeniouty can be defined as 1-D\n",
    "#\n",
    "# Here we plot the homegeniouty of segments from the first word to each subsequent word in the text.\n",
    "\n",
    "plt.plot(1-seg_obj.avg_dist[0,:])\n",
    "plt.ylabel('Homogeniouty (higher is better)')\n",
    "plt.xlabel('word position')\n",
    "plt.title('Homogeniouty of segment from first word to \\'word position\\' ')\n",
    "plt.plot(1-seg_obj.avg_dist[50,:])\n",
    "plt.plot(1-seg_obj.avg_dist[23,:])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "segments= seg_obj.get_segment_texts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "segment 1:\n",
      "Chemical reaction , a process in which one or more substances , the reactants , are converted to one or more different substances , the products . Substances are either chemical elements or compounds . A chemical reaction rearranges the constituent atoms of the reactants to create different substances as products . Chemical reactions are an integral part of technology , of culture , and indeed of life itself . Burning fuels , smelting iron , making glass and pottery , brewing beer , and making wine and cheese are among many examples of activities incorporating chemical reactions that have been known and used for thousands of years . Chemical reactions abound in the geology of Earth , in the atmosphere and oceans , and in a vast array of complicated processes that occur in all living systems . Chemical reactions\n",
      "====\n",
      "segment 2:\n",
      "must be distinguished from physical changes . Physical changes include changes of state , such as ice melting to water and water evaporating to vapour . If a physical change occurs , the physical properties of a substance will change , but its chemical identity will remain the same . No matter what its physical state , water ( H2O ) is the same compound , with each molecule composed of two atoms of hydrogen and one atom of oxygen . However , if water , as ice\n",
      "====\n",
      "segment 3:\n",
      ", liquid , or vapour , encounters sodium metal ( Na ) , the atoms will be redistributed to give the new substances molecular hydrogen ( H2 ) and sodium hydroxide ( NaOH ) . By this , we know that a chemical change or reaction has occurred .\n",
      "====\n"
     ]
    }
   ],
   "source": [
    "for i, seg in enumerate(segments):\n",
    "    print(\"segment {}:\\n{}\\n====\".format(i+1, seg))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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   "language": "python",
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