stemming&lemma.ipynb

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        "id": "p236VWElALW3"
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      "source": [
        "import re \n",
        "import nltk\n",
        "# nltk stemmer\n",
        "from nltk.stem.porter import PorterStemmer\n",
        "from nltk.stem import WordNetLemmatizer\n",
        "nltk.download('all')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def stem(phrase):\n",
        "  return ' '.join([re.findall('^(.*ss|.*?)(s)?$',word)[0][0].strip(\"'\") for word in phrase.lower().split()])\n",
        "\n",
        "stem(\"houses\")"
      ],
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      },
      "execution_count": 23,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'house'"
            ],
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              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "stem(\"cats\")"
      ],
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        },
        "id": "taA38iVvAdwl",
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      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'cat'"
            ],
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              "type": "string"
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          },
          "metadata": {},
          "execution_count": 24
        }
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    },
    {
      "cell_type": "code",
      "source": [
        "stem(\"Doctor House's calls\")"
      ],
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        },
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      },
      "execution_count": 25,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'doctor house call'"
            ],
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              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "stem(\"dishes\")"
      ],
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        },
        "id": "GK_heX2wApVk",
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      "execution_count": 26,
      "outputs": [
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            "text/plain": [
              "'dishe'"
            ],
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          "metadata": {},
          "execution_count": 26
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    },
    {
      "cell_type": "code",
      "source": [
        "stem(\"heroes\")"
      ],
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          "height": 36
        },
        "id": "w68bblAiA8YC",
        "outputId": "38e779d9-5d72-4b3c-9a05-f2b67f65493b"
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      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'heroe'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "stemmer = PorterStemmer()\n",
        "def from_nltk_stemming(sent):\n",
        "  return ' '.join([stemmer.stem(w).strip(\"'\") for w in sent.split()])"
      ],
      "metadata": {
        "id": "96Jx129_BBXD"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from_nltk_stemming(\"the housing is doing very well\")"
      ],
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        },
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      "execution_count": 29,
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            "text/plain": [
              "'the hous is do veri well'"
            ],
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              "type": "string"
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          },
          "metadata": {},
          "execution_count": 29
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      ]
    },
    {
      "cell_type": "code",
      "source": [
        "lemmatizer = WordNetLemmatizer()\n",
        "lemmatizer.lemmatize(\"better\")"
      ],
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      "execution_count": 32,
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        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'better'"
            ],
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              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 32
        }
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    },
    {
      "cell_type": "code",
      "source": [
        "lemmatizer.lemmatize(\"better\", pos=\"a\")"
      ],
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      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'good'"
            ],
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          },
          "metadata": {},
          "execution_count": 33
        }
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    },
    {
      "cell_type": "code",
      "source": [
        "lemmatizer.lemmatize(\"goodness\", pos=\"n\")"
      ],
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      "execution_count": 34,
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          "output_type": "execute_result",
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            "text/plain": [
              "'goodness'"
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          "execution_count": 34
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