{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "initial_id",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:02:01.021005Z",
     "start_time": "2024-12-01T15:01:58.161848Z"
    },
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import itertools\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from collections import Counter\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from sklearn.preprocessing import MultiLabelBinarizer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9b91b6a97eb2b9be",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:02:57.510795Z",
     "start_time": "2024-12-01T15:02:01.039033Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1259417, 7)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>book_id</th>\n",
       "      <th>title</th>\n",
       "      <th>description</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>publisher</th>\n",
       "      <th>authors</th>\n",
       "      <th>similar_books</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1333909</td>\n",
       "      <td>Good Harbor</td>\n",
       "      <td>Anita Diamant's international bestseller \"The ...</td>\n",
       "      <td>2001</td>\n",
       "      <td>Simon &amp; Schuster Audio</td>\n",
       "      <td>[626222]</td>\n",
       "      <td>[8709549, 17074050, 28937, 158816, 228563, 112...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7327624</td>\n",
       "      <td>The Unschooled Wizard (Sun Wolf and Starhawk, ...</td>\n",
       "      <td>Omnibus book club edition containing the Ladie...</td>\n",
       "      <td>1987</td>\n",
       "      <td>Nelson Doubleday, Inc.</td>\n",
       "      <td>[10333]</td>\n",
       "      <td>[19997, 828466, 1569323, 425389, 1176674, 2627...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6066819</td>\n",
       "      <td>Best Friends Forever</td>\n",
       "      <td>Addie Downs and Valerie Adler were eight when ...</td>\n",
       "      <td>2009</td>\n",
       "      <td>Atria Books</td>\n",
       "      <td>[9212]</td>\n",
       "      <td>[6604176, 6054190, 2285777, 82641, 7569453, 70...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>287141</td>\n",
       "      <td>The Aeneid for Boys and Girls</td>\n",
       "      <td>Relates in vigorous prose the tale of Aeneas, ...</td>\n",
       "      <td>2006</td>\n",
       "      <td>Yesterday's Classics</td>\n",
       "      <td>[3041852]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6066812</td>\n",
       "      <td>All's Fairy in Love and War (Avalon: Web of Ma...</td>\n",
       "      <td>To Kara's astonishment, she discovers that a p...</td>\n",
       "      <td>2009</td>\n",
       "      <td>Seven Seas</td>\n",
       "      <td>[19158]</td>\n",
       "      <td>[948696, 439885, 274955, 12978730, 372986, 216...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   book_id                                              title  \\\n",
       "0  1333909                                        Good Harbor   \n",
       "1  7327624  The Unschooled Wizard (Sun Wolf and Starhawk, ...   \n",
       "2  6066819                               Best Friends Forever   \n",
       "3   287141                      The Aeneid for Boys and Girls   \n",
       "4  6066812  All's Fairy in Love and War (Avalon: Web of Ma...   \n",
       "\n",
       "                                         description  publication_year  \\\n",
       "0  Anita Diamant's international bestseller \"The ...              2001   \n",
       "1  Omnibus book club edition containing the Ladie...              1987   \n",
       "2  Addie Downs and Valerie Adler were eight when ...              2009   \n",
       "3  Relates in vigorous prose the tale of Aeneas, ...              2006   \n",
       "4  To Kara's astonishment, she discovers that a p...              2009   \n",
       "\n",
       "                publisher    authors  \\\n",
       "0  Simon & Schuster Audio   [626222]   \n",
       "1  Nelson Doubleday, Inc.    [10333]   \n",
       "2             Atria Books     [9212]   \n",
       "3    Yesterday's Classics  [3041852]   \n",
       "4              Seven Seas    [19158]   \n",
       "\n",
       "                                       similar_books  \n",
       "0  [8709549, 17074050, 28937, 158816, 228563, 112...  \n",
       "1  [19997, 828466, 1569323, 425389, 1176674, 2627...  \n",
       "2  [6604176, 6054190, 2285777, 82641, 7569453, 70...  \n",
       "3                                                 []  \n",
       "4  [948696, 439885, 274955, 12978730, 372986, 216...  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('goodreads_books.csv')\n",
    "df = df[df['title'].notna()]\n",
    "df['authors'] =df['authors'].apply(eval)\n",
    "df['similar_books'] =df['similar_books'].apply(eval)\n",
    "print(df.shape)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6ca5d8672eb45020",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:02:59.577742Z",
     "start_time": "2024-12-01T15:02:57.692112Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of books that have similar books 640364\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>book_id</th>\n",
       "      <th>title</th>\n",
       "      <th>description</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>publisher</th>\n",
       "      <th>authors</th>\n",
       "      <th>similar_books</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1333909</td>\n",
       "      <td>Good Harbor</td>\n",
       "      <td>Anita Diamant's international bestseller \"The ...</td>\n",
       "      <td>2001</td>\n",
       "      <td>Simon &amp; Schuster Audio</td>\n",
       "      <td>[626222]</td>\n",
       "      <td>[8709549, 17074050, 28937, 158816, 228563, 112...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7327624</td>\n",
       "      <td>The Unschooled Wizard (Sun Wolf and Starhawk, ...</td>\n",
       "      <td>Omnibus book club edition containing the Ladie...</td>\n",
       "      <td>1987</td>\n",
       "      <td>Nelson Doubleday, Inc.</td>\n",
       "      <td>[10333]</td>\n",
       "      <td>[19997, 828466, 1569323, 425389, 1176674, 2627...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6066819</td>\n",
       "      <td>Best Friends Forever</td>\n",
       "      <td>Addie Downs and Valerie Adler were eight when ...</td>\n",
       "      <td>2009</td>\n",
       "      <td>Atria Books</td>\n",
       "      <td>[9212]</td>\n",
       "      <td>[6604176, 6054190, 2285777, 82641, 7569453, 70...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>6066812</td>\n",
       "      <td>All's Fairy in Love and War (Avalon: Web of Ma...</td>\n",
       "      <td>To Kara's astonishment, she discovers that a p...</td>\n",
       "      <td>2009</td>\n",
       "      <td>Seven Seas</td>\n",
       "      <td>[19158]</td>\n",
       "      <td>[948696, 439885, 274955, 12978730, 372986, 216...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>287149</td>\n",
       "      <td>The Devil's Notebook</td>\n",
       "      <td>Wisdom, humor, and dark observations by the fo...</td>\n",
       "      <td>2000</td>\n",
       "      <td>Feral House</td>\n",
       "      <td>[2983296, 40075]</td>\n",
       "      <td>[287151, 1104760, 1172822, 440292, 287082, 630...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   book_id                                              title  \\\n",
       "0  1333909                                        Good Harbor   \n",
       "1  7327624  The Unschooled Wizard (Sun Wolf and Starhawk, ...   \n",
       "2  6066819                               Best Friends Forever   \n",
       "4  6066812  All's Fairy in Love and War (Avalon: Web of Ma...   \n",
       "6   287149                               The Devil's Notebook   \n",
       "\n",
       "                                         description  publication_year  \\\n",
       "0  Anita Diamant's international bestseller \"The ...              2001   \n",
       "1  Omnibus book club edition containing the Ladie...              1987   \n",
       "2  Addie Downs and Valerie Adler were eight when ...              2009   \n",
       "4  To Kara's astonishment, she discovers that a p...              2009   \n",
       "6  Wisdom, humor, and dark observations by the fo...              2000   \n",
       "\n",
       "                publisher           authors  \\\n",
       "0  Simon & Schuster Audio          [626222]   \n",
       "1  Nelson Doubleday, Inc.           [10333]   \n",
       "2             Atria Books            [9212]   \n",
       "4              Seven Seas           [19158]   \n",
       "6             Feral House  [2983296, 40075]   \n",
       "\n",
       "                                       similar_books  \n",
       "0  [8709549, 17074050, 28937, 158816, 228563, 112...  \n",
       "1  [19997, 828466, 1569323, 425389, 1176674, 2627...  \n",
       "2  [6604176, 6054190, 2285777, 82641, 7569453, 70...  \n",
       "4  [948696, 439885, 274955, 12978730, 372986, 216...  \n",
       "6  [287151, 1104760, 1172822, 440292, 287082, 630...  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "has_similar_books1 = df['similar_books'].apply(len) > 0\n",
    "has_similar_books1.head()\n",
    "\n",
    "all_similar_books = np.array(list(itertools.chain(*(df['similar_books'].values))))\n",
    "has_similar_books2 = np.isin(df['book_id'], all_similar_books)\n",
    "\n",
    "has_similar_books = has_similar_books1 | has_similar_books2\n",
    "\n",
    "df = df[has_similar_books]\n",
    "print('Number of books that have similar books', df.shape[0])\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6846b3dccaf40875",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d239e42cfd34de80",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:02:59.627408Z",
     "start_time": "2024-12-01T15:02:59.621594Z"
    }
   },
   "outputs": [],
   "source": [
    "data = {}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cffdf6de4137a3a0",
   "metadata": {},
   "source": [
    "## Labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d3b34765c70b3dc0",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:23.519314Z",
     "start_time": "2024-12-01T15:02:59.779801Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>book_id</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5333265</td>\n",
       "      <td>[history, historical fiction, biography]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1333909</td>\n",
       "      <td>[history, historical fiction, biography]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7327624</td>\n",
       "      <td>[fantasy, paranormal, mystery, thriller, crime...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6066819</td>\n",
       "      <td>[romance, mystery, thriller, crime]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>287141</td>\n",
       "      <td>[history, historical fiction, biography, child...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   book_id                                             genres\n",
       "0  5333265           [history, historical fiction, biography]\n",
       "1  1333909           [history, historical fiction, biography]\n",
       "2  7327624  [fantasy, paranormal, mystery, thriller, crime...\n",
       "3  6066819                [romance, mystery, thriller, crime]\n",
       "4   287141  [history, historical fiction, biography, child..."
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "genres = pd.read_csv('goodreads_book_genres_initial.csv')\n",
    "genres['genres'] = genres['genres'].apply(eval)\n",
    "genres.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "55c11b0fe27fe6e8",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:25.895897Z",
     "start_time": "2024-12-01T15:03:23.616794Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(594484, 8)\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>book_id</th>\n",
       "      <th>title</th>\n",
       "      <th>description</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>publisher</th>\n",
       "      <th>authors</th>\n",
       "      <th>similar_books</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1333909</td>\n",
       "      <td>Good Harbor</td>\n",
       "      <td>Anita Diamant's international bestseller \"The ...</td>\n",
       "      <td>2001</td>\n",
       "      <td>Simon &amp; Schuster Audio</td>\n",
       "      <td>[626222]</td>\n",
       "      <td>[8709549, 17074050, 28937, 158816, 228563, 112...</td>\n",
       "      <td>[history, historical fiction, biography]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7327624</td>\n",
       "      <td>The Unschooled Wizard (Sun Wolf and Starhawk, ...</td>\n",
       "      <td>Omnibus book club edition containing the Ladie...</td>\n",
       "      <td>1987</td>\n",
       "      <td>Nelson Doubleday, Inc.</td>\n",
       "      <td>[10333]</td>\n",
       "      <td>[19997, 828466, 1569323, 425389, 1176674, 2627...</td>\n",
       "      <td>[fantasy, paranormal, mystery, thriller, crime...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6066819</td>\n",
       "      <td>Best Friends Forever</td>\n",
       "      <td>Addie Downs and Valerie Adler were eight when ...</td>\n",
       "      <td>2009</td>\n",
       "      <td>Atria Books</td>\n",
       "      <td>[9212]</td>\n",
       "      <td>[6604176, 6054190, 2285777, 82641, 7569453, 70...</td>\n",
       "      <td>[romance, mystery, thriller, crime]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6066812</td>\n",
       "      <td>All's Fairy in Love and War (Avalon: Web of Ma...</td>\n",
       "      <td>To Kara's astonishment, she discovers that a p...</td>\n",
       "      <td>2009</td>\n",
       "      <td>Seven Seas</td>\n",
       "      <td>[19158]</td>\n",
       "      <td>[948696, 439885, 274955, 12978730, 372986, 216...</td>\n",
       "      <td>[fantasy, paranormal, young-adult, children]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>287149</td>\n",
       "      <td>The Devil's Notebook</td>\n",
       "      <td>Wisdom, humor, and dark observations by the fo...</td>\n",
       "      <td>2000</td>\n",
       "      <td>Feral House</td>\n",
       "      <td>[2983296, 40075]</td>\n",
       "      <td>[287151, 1104760, 1172822, 440292, 287082, 630...</td>\n",
       "      <td>[history, historical fiction, biography]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   book_id                                              title  \\\n",
       "0  1333909                                        Good Harbor   \n",
       "1  7327624  The Unschooled Wizard (Sun Wolf and Starhawk, ...   \n",
       "2  6066819                               Best Friends Forever   \n",
       "3  6066812  All's Fairy in Love and War (Avalon: Web of Ma...   \n",
       "4   287149                               The Devil's Notebook   \n",
       "\n",
       "                                         description  publication_year  \\\n",
       "0  Anita Diamant's international bestseller \"The ...              2001   \n",
       "1  Omnibus book club edition containing the Ladie...              1987   \n",
       "2  Addie Downs and Valerie Adler were eight when ...              2009   \n",
       "3  To Kara's astonishment, she discovers that a p...              2009   \n",
       "4  Wisdom, humor, and dark observations by the fo...              2000   \n",
       "\n",
       "                publisher           authors  \\\n",
       "0  Simon & Schuster Audio          [626222]   \n",
       "1  Nelson Doubleday, Inc.           [10333]   \n",
       "2             Atria Books            [9212]   \n",
       "3              Seven Seas           [19158]   \n",
       "4             Feral House  [2983296, 40075]   \n",
       "\n",
       "                                       similar_books  \\\n",
       "0  [8709549, 17074050, 28937, 158816, 228563, 112...   \n",
       "1  [19997, 828466, 1569323, 425389, 1176674, 2627...   \n",
       "2  [6604176, 6054190, 2285777, 82641, 7569453, 70...   \n",
       "3  [948696, 439885, 274955, 12978730, 372986, 216...   \n",
       "4  [287151, 1104760, 1172822, 440292, 287082, 630...   \n",
       "\n",
       "                                              genres  \n",
       "0           [history, historical fiction, biography]  \n",
       "1  [fantasy, paranormal, mystery, thriller, crime...  \n",
       "2                [romance, mystery, thriller, crime]  \n",
       "3       [fantasy, paranormal, young-adult, children]  \n",
       "4           [history, historical fiction, biography]  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "books = pd.merge(df, genres, on='book_id', how='left')\n",
    "books = books[~books['genres'].isna()]\n",
    "books = books[books['genres'].apply(len)>0]\n",
    "print(books.shape)\n",
    "books.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c0a46d2d54eadc71",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:27.087963Z",
     "start_time": "2024-12-01T15:03:26.056872Z"
    }
   },
   "outputs": [],
   "source": [
    "label_encoder = MultiLabelBinarizer(sparse_output=True)\n",
    "labels = label_encoder.fit_transform(books['genres']).astype(np.bool_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f30a5996f451165c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:27.164320Z",
     "start_time": "2024-12-01T15:03:27.157773Z"
    }
   },
   "outputs": [],
   "source": [
    "data['book_labels'] = labels"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd38e5df5bf7243c",
   "metadata": {},
   "source": [
    "## Book-Author Links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6ee5abdfe0caf84",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:28.025301Z",
     "start_time": "2024-12-01T15:03:27.250118Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of authors 147863\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>author</th>\n",
       "      <th>count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>123715</td>\n",
       "      <td>2000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3389</td>\n",
       "      <td>1739</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>359</th>\n",
       "      <td>3780</td>\n",
       "      <td>1544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2111</th>\n",
       "      <td>947</td>\n",
       "      <td>1418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1534</th>\n",
       "      <td>625</td>\n",
       "      <td>1209</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      author  count\n",
       "18    123715   2000\n",
       "9       3389   1739\n",
       "359     3780   1544\n",
       "2111     947   1418\n",
       "1534     625   1209"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "authors = list(itertools.chain(*(books['authors'].values)))\n",
    "author_count_dict = Counter(authors)\n",
    "author_count_df = pd.DataFrame(list(author_count_dict.items()), columns=['author', 'count'])\n",
    "print('Number of authors', author_count_df.shape[0])\n",
    "author_count_df.sort_values(by='count', ascending=False).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f8fdc6fae6ed6a11",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:31.862308Z",
     "start_time": "2024-12-01T15:03:28.116806Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of book-author links: 826369\n"
     ]
    }
   ],
   "source": [
    "book_ids = np.concatenate([np.full(count, i) \n",
    "                                 for i, count in enumerate(books['authors'].apply(len))])\n",
    "\n",
    "author_id_encoder = LabelEncoder()\n",
    "author_ids = author_id_encoder.fit_transform(authors).astype(np.int32)\n",
    "\n",
    "print('Number of book-author links:', author_ids.shape[0])\n",
    "\n",
    "data['book-author'] = (book_ids, author_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a5a30970b7fae165",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "1380cf57160349e2",
   "metadata": {},
   "source": [
    "## Book-Publisher Links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "243f23406fe1c845",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:32.182494Z",
     "start_time": "2024-12-01T15:03:31.968836Z"
    }
   },
   "outputs": [],
   "source": [
    "books['publisher'] = books['publisher'].str.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "36d25bd5e5d2b5ae",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:32.942637Z",
     "start_time": "2024-12-01T15:03:32.260068Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of publishers: 43910\n"
     ]
    }
   ],
   "source": [
    "publisher_id_encoder = LabelEncoder()\n",
    "publisher_ids = publisher_id_encoder.fit_transform(books['publisher'])\n",
    "print('Number of publishers:', publisher_ids.max()+1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "14631f9a7bb9eb09",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:32.972437Z",
     "start_time": "2024-12-01T15:03:32.962111Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of book-publisher links: 594484\n"
     ]
    }
   ],
   "source": [
    "book_ids = np.arange(books.shape[0])\n",
    "publisher_ids = publisher_ids.astype(np.uint16)\n",
    "\n",
    "print('Number of book-publisher links:', publisher_ids.shape[0])\n",
    "data['book-publisher'] = (book_ids, publisher_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6a7f6d07b544bcfb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "5881666538c61e9b",
   "metadata": {},
   "source": [
    "## Book-Book Links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "c3fae65aa006b6b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:33.241692Z",
     "start_time": "2024-12-01T15:03:33.214832Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>book_id</th>\n",
       "      <th>title</th>\n",
       "      <th>description</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>publisher</th>\n",
       "      <th>authors</th>\n",
       "      <th>similar_books</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1333909</td>\n",
       "      <td>Good Harbor</td>\n",
       "      <td>Anita Diamant's international bestseller \"The ...</td>\n",
       "      <td>2001</td>\n",
       "      <td>simon &amp; schuster audio</td>\n",
       "      <td>[626222]</td>\n",
       "      <td>[8709549, 17074050, 28937, 158816, 228563, 112...</td>\n",
       "      <td>[history, historical fiction, biography]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7327624</td>\n",
       "      <td>The Unschooled Wizard (Sun Wolf and Starhawk, ...</td>\n",
       "      <td>Omnibus book club edition containing the Ladie...</td>\n",
       "      <td>1987</td>\n",
       "      <td>nelson doubleday, inc.</td>\n",
       "      <td>[10333]</td>\n",
       "      <td>[19997, 828466, 1569323, 425389, 1176674, 2627...</td>\n",
       "      <td>[fantasy, paranormal, mystery, thriller, crime...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6066819</td>\n",
       "      <td>Best Friends Forever</td>\n",
       "      <td>Addie Downs and Valerie Adler were eight when ...</td>\n",
       "      <td>2009</td>\n",
       "      <td>atria books</td>\n",
       "      <td>[9212]</td>\n",
       "      <td>[6604176, 6054190, 2285777, 82641, 7569453, 70...</td>\n",
       "      <td>[romance, mystery, thriller, crime]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6066812</td>\n",
       "      <td>All's Fairy in Love and War (Avalon: Web of Ma...</td>\n",
       "      <td>To Kara's astonishment, she discovers that a p...</td>\n",
       "      <td>2009</td>\n",
       "      <td>seven seas</td>\n",
       "      <td>[19158]</td>\n",
       "      <td>[948696, 439885, 274955, 12978730, 372986, 216...</td>\n",
       "      <td>[fantasy, paranormal, young-adult, children]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>287149</td>\n",
       "      <td>The Devil's Notebook</td>\n",
       "      <td>Wisdom, humor, and dark observations by the fo...</td>\n",
       "      <td>2000</td>\n",
       "      <td>feral house</td>\n",
       "      <td>[2983296, 40075]</td>\n",
       "      <td>[287151, 1104760, 1172822, 440292, 287082, 630...</td>\n",
       "      <td>[history, historical fiction, biography]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   book_id                                              title  \\\n",
       "0  1333909                                        Good Harbor   \n",
       "1  7327624  The Unschooled Wizard (Sun Wolf and Starhawk, ...   \n",
       "2  6066819                               Best Friends Forever   \n",
       "3  6066812  All's Fairy in Love and War (Avalon: Web of Ma...   \n",
       "4   287149                               The Devil's Notebook   \n",
       "\n",
       "                                         description  publication_year  \\\n",
       "0  Anita Diamant's international bestseller \"The ...              2001   \n",
       "1  Omnibus book club edition containing the Ladie...              1987   \n",
       "2  Addie Downs and Valerie Adler were eight when ...              2009   \n",
       "3  To Kara's astonishment, she discovers that a p...              2009   \n",
       "4  Wisdom, humor, and dark observations by the fo...              2000   \n",
       "\n",
       "                publisher           authors  \\\n",
       "0  simon & schuster audio          [626222]   \n",
       "1  nelson doubleday, inc.           [10333]   \n",
       "2             atria books            [9212]   \n",
       "3              seven seas           [19158]   \n",
       "4             feral house  [2983296, 40075]   \n",
       "\n",
       "                                       similar_books  \\\n",
       "0  [8709549, 17074050, 28937, 158816, 228563, 112...   \n",
       "1  [19997, 828466, 1569323, 425389, 1176674, 2627...   \n",
       "2  [6604176, 6054190, 2285777, 82641, 7569453, 70...   \n",
       "3  [948696, 439885, 274955, 12978730, 372986, 216...   \n",
       "4  [287151, 1104760, 1172822, 440292, 287082, 630...   \n",
       "\n",
       "                                              genres  \n",
       "0           [history, historical fiction, biography]  \n",
       "1  [fantasy, paranormal, mystery, thriller, crime...  \n",
       "2                [romance, mystery, thriller, crime]  \n",
       "3       [fantasy, paranormal, young-adult, children]  \n",
       "4           [history, historical fiction, biography]  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "books.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1b5c2f8770c233c1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:37.317930Z",
     "start_time": "2024-12-01T15:03:33.565952Z"
    }
   },
   "outputs": [],
   "source": [
    "book_ids = np.concatenate([np.full(count, i) \n",
    "                                 for i, count in enumerate(books['similar_books'].apply(len))])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d9a0f2ea5eafc2b7",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:38.723310Z",
     "start_time": "2024-12-01T15:03:37.413450Z"
    }
   },
   "outputs": [],
   "source": [
    "similar_book_ids = np.array(list(itertools.chain(*(books['similar_books'].values))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "98d12cf75643deb5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:39.188161Z",
     "start_time": "2024-12-01T15:03:38.734349Z"
    }
   },
   "outputs": [],
   "source": [
    "mask = np.isin(similar_book_ids, books['book_id'].values)\n",
    "book_ids = book_ids[mask]\n",
    "similar_book_ids = similar_book_ids[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "71668c7c67f579a1",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:48.529895Z",
     "start_time": "2024-12-01T15:03:39.420886Z"
    }
   },
   "outputs": [],
   "source": [
    "book_id_map = dict(zip(books['book_id'].values, range(len(book_ids))))\n",
    "similar_book_ids = np.array([book_id_map[_] for _ in similar_book_ids])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fbfc9064c9306926",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:49.570122Z",
     "start_time": "2024-12-01T15:03:49.436004Z"
    }
   },
   "outputs": [],
   "source": [
    "# Save memory\n",
    "mask = book_ids < similar_book_ids\n",
    "book_ids = book_ids[mask]\n",
    "similar_book_ids = similar_book_ids[mask]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "8edc9d69e5eadb21",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:50.457376Z",
     "start_time": "2024-12-01T15:03:50.449784Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of book-book links: 3510209\n"
     ]
    }
   ],
   "source": [
    "print('Number of book-book links:', similar_book_ids.shape[0])\n",
    "data['book-book'] = (book_ids, similar_book_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8cc7b055644c1d42",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "32ff5477051870d5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:51.333417Z",
     "start_time": "2024-12-01T15:03:51.323284Z"
    }
   },
   "outputs": [],
   "source": [
    "book_years = (books['publication_year']).values.astype(np.int16)\n",
    "data['book_years'] = book_years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "3f59be40f4948310",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:52.244019Z",
     "start_time": "2024-12-01T15:03:52.229147Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'book_labels': <Compressed Sparse Row sparse matrix of dtype 'bool'\n",
       " \twith 1304440 stored elements and shape (594484, 8)>,\n",
       " 'book-author': (array([     0,      1,      2, ..., 594482, 594482, 594483]),\n",
       "  array([ 53976,   3557,   3138, ...,    784,  81819, 128754])),\n",
       " 'book-publisher': (array([     0,      1,      2, ..., 594481, 594482, 594483]),\n",
       "  array([36145, 27416,  2948, ..., 16709, 27036, 16233], dtype=uint16)),\n",
       " 'book-book': (array([     0,      0,      0, ..., 594468, 594476, 594476]),\n",
       "  array([236765, 406277, 529992, ..., 594479, 594481, 594479])),\n",
       " 'book_years': array([2001, 1987, 2009, ..., 2007, 2015, 2014], dtype=int16)}"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "a0867ffd9f4ee3f9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T15:03:53.251143Z",
     "start_time": "2024-12-01T15:03:53.174887Z"
    }
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "with open('book.pkl', 'wb') as f:\n",
    "    pickle.dump(data, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "1d4bf279de35c717",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2024-12-01T14:30:28.500440Z",
     "start_time": "2024-12-01T14:30:18.334222Z"
    }
   },
   "outputs": [],
   "source": [
    "books.to_csv('Book.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7487e86adadcaec",
   "metadata": {},
   "source": [
    "### Node Features\n",
    "\n",
    "We generate embeddings as features for each node in the graph. Node embeddings are generated by passing the title and the description through a Sentence-BERT model and obtaining a 384-embedding vector for each movie node.\n",
    "\n",
    "\n",
    "According to [Sentence-Transformers docs](https://www.sbert.net/docs/pretrained_models.html), the **all-MiniLM-L6-v2** model provides the best quality. So we use it to generate node features.\n",
    "\n",
    "all-MiniLM-L6-v2\n",
    "\n",
    "Description:\tAll-round model tuned for many use-cases. Trained on a large and diverse dataset of over 1 billion training pairs.\n",
    "Base Model:\tnreimers/MiniLM-L6-H384-uncased\n",
    "Max Sequence Length:\t256\n",
    "Dimensions:\t384\n",
    "Normalized Embeddings:\ttrue\n",
    "Suitable Score Functions:\tdot-product (util.dot_score), cosine-similarity (util.cos_sim), euclidean distance\n",
    "Size:\t80 MB\n",
    "Pooling:\tMean Pooling\n",
    "Training Data:\t1B+ training pairs. For details, see model card.\n",
    "Model Card:\thttps://huggingface.co/sentence-transformers/all-MiniLM-L6-v2\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "15e53898382782a0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>book_id</th>\n",
       "      <th>title</th>\n",
       "      <th>description</th>\n",
       "      <th>publication_year</th>\n",
       "      <th>publisher</th>\n",
       "      <th>authors</th>\n",
       "      <th>similar_books</th>\n",
       "      <th>genres</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1333909</td>\n",
       "      <td>Good Harbor</td>\n",
       "      <td>Anita Diamant's international bestseller \"The ...</td>\n",
       "      <td>2001</td>\n",
       "      <td>simon &amp; schuster audio</td>\n",
       "      <td>[626222]</td>\n",
       "      <td>[8709549, 17074050, 28937, 158816, 228563, 112...</td>\n",
       "      <td>['history, historical fiction, biography']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7327624</td>\n",
       "      <td>The Unschooled Wizard (Sun Wolf and Starhawk, ...</td>\n",
       "      <td>Omnibus book club edition containing the Ladie...</td>\n",
       "      <td>1987</td>\n",
       "      <td>nelson doubleday, inc.</td>\n",
       "      <td>[10333]</td>\n",
       "      <td>[19997, 828466, 1569323, 425389, 1176674, 2627...</td>\n",
       "      <td>['fantasy, paranormal', 'mystery, thriller, cr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6066819</td>\n",
       "      <td>Best Friends Forever</td>\n",
       "      <td>Addie Downs and Valerie Adler were eight when ...</td>\n",
       "      <td>2009</td>\n",
       "      <td>atria books</td>\n",
       "      <td>[9212]</td>\n",
       "      <td>[6604176, 6054190, 2285777, 82641, 7569453, 70...</td>\n",
       "      <td>['romance', 'mystery, thriller, crime']</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>6066812</td>\n",
       "      <td>All's Fairy in Love and War (Avalon: Web of Ma...</td>\n",
       "      <td>To Kara's astonishment, she discovers that a p...</td>\n",
       "      <td>2009</td>\n",
       "      <td>seven seas</td>\n",
       "      <td>[19158]</td>\n",
       "      <td>[948696, 439885, 274955, 12978730, 372986, 216...</td>\n",
       "      <td>['fantasy, paranormal', 'young-adult', 'childr...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>287149</td>\n",
       "      <td>The Devil's Notebook</td>\n",
       "      <td>Wisdom, humor, and dark observations by the fo...</td>\n",
       "      <td>2000</td>\n",
       "      <td>feral house</td>\n",
       "      <td>[2983296, 40075]</td>\n",
       "      <td>[287151, 1104760, 1172822, 440292, 287082, 630...</td>\n",
       "      <td>['history, historical fiction, biography']</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   book_id                                              title  \\\n",
       "0  1333909                                        Good Harbor   \n",
       "1  7327624  The Unschooled Wizard (Sun Wolf and Starhawk, ...   \n",
       "2  6066819                               Best Friends Forever   \n",
       "3  6066812  All's Fairy in Love and War (Avalon: Web of Ma...   \n",
       "4   287149                               The Devil's Notebook   \n",
       "\n",
       "                                         description  publication_year  \\\n",
       "0  Anita Diamant's international bestseller \"The ...              2001   \n",
       "1  Omnibus book club edition containing the Ladie...              1987   \n",
       "2  Addie Downs and Valerie Adler were eight when ...              2009   \n",
       "3  To Kara's astonishment, she discovers that a p...              2009   \n",
       "4  Wisdom, humor, and dark observations by the fo...              2000   \n",
       "\n",
       "                publisher           authors  \\\n",
       "0  simon & schuster audio          [626222]   \n",
       "1  nelson doubleday, inc.           [10333]   \n",
       "2             atria books            [9212]   \n",
       "3              seven seas           [19158]   \n",
       "4             feral house  [2983296, 40075]   \n",
       "\n",
       "                                       similar_books  \\\n",
       "0  [8709549, 17074050, 28937, 158816, 228563, 112...   \n",
       "1  [19997, 828466, 1569323, 425389, 1176674, 2627...   \n",
       "2  [6604176, 6054190, 2285777, 82641, 7569453, 70...   \n",
       "3  [948696, 439885, 274955, 12978730, 372986, 216...   \n",
       "4  [287151, 1104760, 1172822, 440292, 287082, 630...   \n",
       "\n",
       "                                              genres  \n",
       "0         ['history, historical fiction, biography']  \n",
       "1  ['fantasy, paranormal', 'mystery, thriller, cr...  \n",
       "2            ['romance', 'mystery, thriller, crime']  \n",
       "3  ['fantasy, paranormal', 'young-adult', 'childr...  \n",
       "4         ['history, historical fiction, biography']  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "books = pd.read_csv('Book.csv')\n",
    "books.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b3cfbb60",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'book_labels': <Compressed Sparse Row sparse matrix of dtype 'bool'\n",
       " \twith 1304440 stored elements and shape (594484, 8)>,\n",
       " 'book-author': (array([     0,      1,      2, ..., 594482, 594482, 594483], dtype=int32),\n",
       "  array([ 53976,   3557,   3138, ...,    784,  81819, 128754], dtype=int32)),\n",
       " 'book-publisher': (array([     0,      1,      2, ..., 594481, 594482, 594483], dtype=int32),\n",
       "  array([36145, 27416,  2948, ..., 16709, 27036, 16233], dtype=uint16)),\n",
       " 'book-book': (array([     0,      0,      0, ..., 594468, 594476, 594476], dtype=int32),\n",
       "  array([236765, 406277, 529992, ..., 594479, 594481, 594479], dtype=int32)),\n",
       " 'book_years': array([2001, 1987, 2009, ..., 2007, 2015, 2014], dtype=int16)}"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pickle\n",
    "\n",
    "with open('book.pkl', 'rb') as f:\n",
    "    data = pickle.load(f)\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "7bd49dd4",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "SentenceTransformer(\n",
       "  (0): Transformer({'max_seq_length': 256, 'do_lower_case': False}) with Transformer model: BertModel \n",
       "  (1): Pooling({'word_embedding_dimension': 384, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})\n",
       "  (2): Normalize()\n",
       ")"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torch\n",
    "from sentence_transformers import SentenceTransformer\n",
    "\n",
    "device = 'cuda:0' if torch.cuda.is_available() else 'cpu'\n",
    "model = SentenceTransformer('../sentence-transformers/all-MiniLM-L6-v2', device=device)\n",
    "model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b86eb9fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "text = books['title'] + ' ' + books['description']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ab1586ef",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Batches: 100%|██████████| 146/146 [07:21<00:00,  3.02s/it]\n"
     ]
    }
   ],
   "source": [
    "feats = model.encode(text, batch_size=4096, show_progress_bar=True, convert_to_numpy=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "f6b5c92e",
   "metadata": {},
   "outputs": [],
   "source": [
    "data['book_feats'] = feats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "497721b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('book.pkl', 'wb') as f:\n",
    "    pickle.dump(data, f)"
   ]
  }
 ],
 "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",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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