{
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  {
   "cell_type": "markdown",
   "id": "4f0923c7-3ebb-4809-8015-0aff4a04569c",
   "metadata": {},
   "source": [
    "# Text normalization\n",
    "* To relate variations of words to a common form/root, e.g.\n",
    "\n",
    "    run, runs, running -> run<br>\n",
    "    am, are, is -> be\n",
    "* Includes both stemming and lemmatization\n",
    "* Need to consider both inflectional forms and derivational forms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "3135d8e9-c434-4fb1-b1dc-b51e3077f60a",
   "metadata": {},
   "outputs": [],
   "source": [
    "import nltk"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "ddc9f631-2624-456b-8c40-857bcc9a41a0",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[nltk_data] Downloading package wordnet to C:\\nltk_data...\n",
      "[nltk_data]   Package wordnet is already up-to-date!\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from nltk.stem import PorterStemmer, WordNetLemmatizer\n",
    "from nltk import wordnet\n",
    "nltk.download('wordnet')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "52346f65-74e0-4b2f-87bb-d0284ea3f99b",
   "metadata": {},
   "outputs": [],
   "source": [
    "stemmer = PorterStemmer()\n",
    "wnl = WordNetLemmatizer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f57a43a1-368f-4642-bb2f-1241d300e608",
   "metadata": {},
   "outputs": [],
   "source": [
    "word = 'meeting'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a33c32b9-4ad2-4e50-bd1c-23d5707f5644",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('meet', 'meeting')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stemmer.stem(word), wnl.lemmatize(word)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4f199f56-1dea-4204-8f4f-2ec3cf8e4937",
   "metadata": {},
   "outputs": [],
   "source": [
    "words1 = ['I', 'am', 'going', 'to', 'a', 'meeting', 'about', 'data', 'science']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ab5e6fef-7968-496a-9624-f9f9437e04e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "words2 = ['dogs', 'churches', 'aardwolves', 'abaci']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "80a461c8-4235-4ddd-9629-c2b717d10319",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['dog', 'church', 'aardwolv', 'abaci']"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[stemmer.stem(word) for word in words2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "e592c511-6121-4af7-92a3-81199e760276",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['dog', 'church', 'aardwolf', 'abacus']"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[wnl.lemmatize(word) for word in words2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8e1509a2-2ad4-4b82-a5c4-cb79527ec8f5",
   "metadata": {},
   "source": [
    "lemmatize did a better job with the made up word"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "50936259-fd59-4b32-9ef6-28dbc011e044",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['i', 'am', 'go', 'to', 'a', 'meet', 'about', 'data', 'scienc']"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[stemmer.stem(word) for word in words1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "e138f7be-80dd-44ae-9777-6effe1f4a12e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['I', 'am', 'going', 'to', 'a', 'meeting', 'about', 'data', 'science']"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[wnl.lemmatize(word) for word in words1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fcd69584-c622-430d-bd44-eab4342dc064",
   "metadata": {},
   "source": [
    "Lemmatization is done in linguistic sensitive contexts, below we'll set it to treat terms as verbs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "3ac7b59d-39d4-41ee-a8b8-a7ae284760af",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['I', 'be', 'go', 'to', 'a', 'meet', 'about', 'data', 'science']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[wnl.lemmatize(word, pos='v') for word in words1]"
   ]
  }
 ],
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