{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "initial_id",
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import itertools\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.preprocessing import LabelEncoder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "775d8173",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1002355, 8)\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>id</th>\n",
       "      <th>title</th>\n",
       "      <th>abstract</th>\n",
       "      <th>year</th>\n",
       "      <th>label</th>\n",
       "      <th>authors</th>\n",
       "      <th>references</th>\n",
       "      <th>fos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1091</td>\n",
       "      <td>Preliminary Design of a Network Protocol Learn...</td>\n",
       "      <td>The purpose of this study is to develop a lear...</td>\n",
       "      <td>2013</td>\n",
       "      <td>6</td>\n",
       "      <td>[2312688602, 2482909946, 2128134587, 210178269...</td>\n",
       "      <td>[2005687710, 2018037215]</td>\n",
       "      <td>[telecommunications network, computer science,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15883</td>\n",
       "      <td>Leveraging legacy code to deploy desktop appli...</td>\n",
       "      <td>Xax is a browser plugin model that enables dev...</td>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>[135218249, 2120803867, 2128381254, 2150137935]</td>\n",
       "      <td>[114793137, 186343359, 205258527, 1516211918, ...</td>\n",
       "      <td>[world wide web, computer science, machine cod...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15901</td>\n",
       "      <td>A pedestrian navigation method for user's safe...</td>\n",
       "      <td>In recent years, most of mobile phones have a ...</td>\n",
       "      <td>2013</td>\n",
       "      <td>6</td>\n",
       "      <td>[2789599552, 2935910818]</td>\n",
       "      <td>[2055819696, 2167564737, 2169528473]</td>\n",
       "      <td>[visibility, route planning, computer science,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>38917</td>\n",
       "      <td>Automated Object Identification and Position E...</td>\n",
       "      <td>The development of an automated system for the...</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "      <td>[2068146743, 2252543171, 1278895136, 2171534607]</td>\n",
       "      <td>[96589161, 2138661420, 2157641950, 2163004336,...</td>\n",
       "      <td>[computer vision, aerodrome, image sensor, com...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>58261</td>\n",
       "      <td>A general semantic analyser for data base access</td>\n",
       "      <td>The paper discusses the design principles and ...</td>\n",
       "      <td>1981</td>\n",
       "      <td>0</td>\n",
       "      <td>[2316496857, 2169254595]</td>\n",
       "      <td>[1997320166, 2042008249, 2043794661, 2061141062]</td>\n",
       "      <td>[front and back ends, design elements and prin...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id                                              title  \\\n",
       "0   1091  Preliminary Design of a Network Protocol Learn...   \n",
       "1  15883  Leveraging legacy code to deploy desktop appli...   \n",
       "2  15901  A pedestrian navigation method for user's safe...   \n",
       "3  38917  Automated Object Identification and Position E...   \n",
       "4  58261   A general semantic analyser for data base access   \n",
       "\n",
       "                                            abstract  year  label  \\\n",
       "0  The purpose of this study is to develop a lear...  2013      6   \n",
       "1  Xax is a browser plugin model that enables dev...  2008      4   \n",
       "2  In recent years, most of mobile phones have a ...  2013      6   \n",
       "3  The development of an automated system for the...  2008      0   \n",
       "4  The paper discusses the design principles and ...  1981      0   \n",
       "\n",
       "                                             authors  \\\n",
       "0  [2312688602, 2482909946, 2128134587, 210178269...   \n",
       "1    [135218249, 2120803867, 2128381254, 2150137935]   \n",
       "2                           [2789599552, 2935910818]   \n",
       "3   [2068146743, 2252543171, 1278895136, 2171534607]   \n",
       "4                           [2316496857, 2169254595]   \n",
       "\n",
       "                                          references  \\\n",
       "0                           [2005687710, 2018037215]   \n",
       "1  [114793137, 186343359, 205258527, 1516211918, ...   \n",
       "2               [2055819696, 2167564737, 2169528473]   \n",
       "3  [96589161, 2138661420, 2157641950, 2163004336,...   \n",
       "4   [1997320166, 2042008249, 2043794661, 2061141062]   \n",
       "\n",
       "                                                 fos  \n",
       "0  [telecommunications network, computer science,...  \n",
       "1  [world wide web, computer science, machine cod...  \n",
       "2  [visibility, route planning, computer science,...  \n",
       "3  [computer vision, aerodrome, image sensor, com...  \n",
       "4  [front and back ends, design elements and prin...  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "papers = pd.read_csv('dblp.v12.csv')\n",
    "papers['authors'] = papers['authors'].apply(eval)\n",
    "papers['references'] = papers['references'].apply(eval)\n",
    "papers['fos'] = papers['fos'].apply(eval)\n",
    "print(papers.shape)\n",
    "papers.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "add9f8dc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(14072159, np.int64(7876504))"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Extend the `references` column to a List[2005687710, 2018037215, 114793137, ...]\n",
    "all_references = np.array(list(itertools.chain(*(papers['references'].values))))\n",
    "\n",
    "# Construct a list containing the `id` corresponding to the above references list\n",
    "paper_ids = np.concatenate([np.full(count, i) \n",
    "                                 for i, count in zip(papers['id'].values, papers['references'].apply(len))])\n",
    "\n",
    "assert len(all_references) == len(paper_ids)\n",
    "\n",
    "# Wether a reference is in the `id` column\n",
    "in_paperids = np.isin(all_references, papers['id'].values)\n",
    "len(in_paperids), in_paperids.sum() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "98a23d01",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filter the references list\n",
    "all_references = all_references[in_paperids]\n",
    "paper_ids = paper_ids[in_paperids]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "a35ac7fd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of papers that refer or are referred 964350\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>id</th>\n",
       "      <th>title</th>\n",
       "      <th>abstract</th>\n",
       "      <th>year</th>\n",
       "      <th>label</th>\n",
       "      <th>authors</th>\n",
       "      <th>references</th>\n",
       "      <th>fos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>15883</td>\n",
       "      <td>Leveraging legacy code to deploy desktop appli...</td>\n",
       "      <td>Xax is a browser plugin model that enables dev...</td>\n",
       "      <td>2008</td>\n",
       "      <td>4</td>\n",
       "      <td>[135218249, 2120803867, 2128381254, 2150137935]</td>\n",
       "      <td>[114793137, 186343359, 205258527, 1516211918, ...</td>\n",
       "      <td>[world wide web, computer science, machine cod...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>15901</td>\n",
       "      <td>A pedestrian navigation method for user's safe...</td>\n",
       "      <td>In recent years, most of mobile phones have a ...</td>\n",
       "      <td>2013</td>\n",
       "      <td>6</td>\n",
       "      <td>[2789599552, 2935910818]</td>\n",
       "      <td>[2055819696, 2167564737, 2169528473]</td>\n",
       "      <td>[visibility, route planning, computer science,...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>38917</td>\n",
       "      <td>Automated Object Identification and Position E...</td>\n",
       "      <td>The development of an automated system for the...</td>\n",
       "      <td>2008</td>\n",
       "      <td>0</td>\n",
       "      <td>[2068146743, 2252543171, 1278895136, 2171534607]</td>\n",
       "      <td>[96589161, 2138661420, 2157641950, 2163004336,...</td>\n",
       "      <td>[computer vision, aerodrome, image sensor, com...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>58261</td>\n",
       "      <td>A general semantic analyser for data base access</td>\n",
       "      <td>The paper discusses the design principles and ...</td>\n",
       "      <td>1981</td>\n",
       "      <td>0</td>\n",
       "      <td>[2316496857, 2169254595]</td>\n",
       "      <td>[1997320166, 2042008249, 2043794661, 2061141062]</td>\n",
       "      <td>[front and back ends, design elements and prin...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>65220</td>\n",
       "      <td>Two notes from experimental study on image ste...</td>\n",
       "      <td>In recent years, several advanced methods for ...</td>\n",
       "      <td>2013</td>\n",
       "      <td>0</td>\n",
       "      <td>[2304723528, 2676058149, 2120394816]</td>\n",
       "      <td>[22271197, 29798142, 1713630528, 1955882805, 2...</td>\n",
       "      <td>[steganography, steganography tools, pattern r...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      id                                              title  \\\n",
       "1  15883  Leveraging legacy code to deploy desktop appli...   \n",
       "2  15901  A pedestrian navigation method for user's safe...   \n",
       "3  38917  Automated Object Identification and Position E...   \n",
       "4  58261   A general semantic analyser for data base access   \n",
       "5  65220  Two notes from experimental study on image ste...   \n",
       "\n",
       "                                            abstract  year  label  \\\n",
       "1  Xax is a browser plugin model that enables dev...  2008      4   \n",
       "2  In recent years, most of mobile phones have a ...  2013      6   \n",
       "3  The development of an automated system for the...  2008      0   \n",
       "4  The paper discusses the design principles and ...  1981      0   \n",
       "5  In recent years, several advanced methods for ...  2013      0   \n",
       "\n",
       "                                            authors  \\\n",
       "1   [135218249, 2120803867, 2128381254, 2150137935]   \n",
       "2                          [2789599552, 2935910818]   \n",
       "3  [2068146743, 2252543171, 1278895136, 2171534607]   \n",
       "4                          [2316496857, 2169254595]   \n",
       "5              [2304723528, 2676058149, 2120394816]   \n",
       "\n",
       "                                          references  \\\n",
       "1  [114793137, 186343359, 205258527, 1516211918, ...   \n",
       "2               [2055819696, 2167564737, 2169528473]   \n",
       "3  [96589161, 2138661420, 2157641950, 2163004336,...   \n",
       "4   [1997320166, 2042008249, 2043794661, 2061141062]   \n",
       "5  [22271197, 29798142, 1713630528, 1955882805, 2...   \n",
       "\n",
       "                                                 fos  \n",
       "1  [world wide web, computer science, machine cod...  \n",
       "2  [visibility, route planning, computer science,...  \n",
       "3  [computer vision, aerodrome, image sensor, com...  \n",
       "4  [front and back ends, design elements and prin...  \n",
       "5  [steganography, steganography tools, pattern r...  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "has_reference1 = np.isin(papers['id'].values, paper_ids)\n",
    "has_reference2 = np.isin(papers['id'].values, all_references)\n",
    "has_reference = has_reference1 | has_reference2\n",
    "papers = papers[has_reference]\n",
    "print('Number of papers that refer or are referred', papers.shape[0])\n",
    "papers.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "140f3a6b",
   "metadata": {},
   "source": [
    "## Paper-Paper Links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "58bc2147",
   "metadata": {},
   "outputs": [],
   "source": [
    "data = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8c8a2b26",
   "metadata": {},
   "outputs": [],
   "source": [
    "paper_id_encoder = LabelEncoder()\n",
    "paper_id_encoder.fit(papers['id'].values)\n",
    "all_references = paper_id_encoder.transform(all_references).astype(np.int32)\n",
    "paper_ids = paper_id_encoder.transform(paper_ids).astype(np.int32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e59e8efe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of paper-paper links: 7876504\n"
     ]
    }
   ],
   "source": [
    "src = np.concatenate((paper_ids, all_references))\n",
    "dst = np.concatenate((all_references, paper_ids))\n",
    "mask = src < dst\n",
    "src = src[mask]\n",
    "dst = dst[mask]\n",
    "\n",
    "print('Number of paper-paper links:', src.shape[0])\n",
    "data['paper-paper'] = (src, dst)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c6ea40b9",
   "metadata": {},
   "source": [
    "## Paper-Author Links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7ac95935",
   "metadata": {},
   "outputs": [],
   "source": [
    "paper_ids = np.concatenate([np.full(count, i) \n",
    "                                 for i, count in zip(papers['id'].values, papers['authors'].apply(len))])\n",
    "authors = list(itertools.chain(*(papers['authors'].values)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "a18d2f9c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of authors: 958961\n"
     ]
    }
   ],
   "source": [
    "author_id_encoder = LabelEncoder()\n",
    "author_ids = author_id_encoder.fit_transform(authors).astype(np.int32)\n",
    "print('Number of authors:', len(author_id_encoder.classes_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c26050f6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of paper-author links: 3070343\n"
     ]
    }
   ],
   "source": [
    "paper_ids = paper_id_encoder.transform(paper_ids).astype(np.int32)\n",
    "assert len(author_ids) == len(paper_ids)\n",
    "print('Number of paper-author links:', paper_ids.shape[0])\n",
    "data['paper-author'] = (paper_ids, author_ids)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dac2cf56",
   "metadata": {},
   "source": [
    "## Paper-FoS Links"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "84c81398",
   "metadata": {},
   "outputs": [],
   "source": [
    "paper_ids = np.concatenate([np.full(count, i) \n",
    "                                 for i, count in zip(papers['id'].values, papers['fos'].apply(len))])\n",
    "foss = list(itertools.chain(*(papers['fos'].values)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "4b01e746",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of FoS: 65699\n"
     ]
    }
   ],
   "source": [
    "fos_id_encoder = LabelEncoder()\n",
    "fos_ids = fos_id_encoder.fit_transform(foss).astype(np.int32)\n",
    "print('Number of FoS:', len(fos_id_encoder.classes_))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "db87e8fe",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of paper-fos links: 10086883\n"
     ]
    }
   ],
   "source": [
    "paper_ids = paper_id_encoder.transform(paper_ids).astype(np.int32)\n",
    "\n",
    "assert len(fos_ids) == len(paper_ids)\n",
    "print('Number of paper-fos links:', fos_ids.shape[0])\n",
    "data['paper-fos'] = (paper_ids, fos_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bfe4abd3",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "59b8e0bf",
   "metadata": {},
   "source": [
    "## Labels and Years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "2f2e6972",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
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       "    .dataframe thead th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>abstract</th>\n",
       "      <th>year</th>\n",
       "      <th>label</th>\n",
       "      <th>authors</th>\n",
       "      <th>references</th>\n",
       "      <th>fos</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>964345</th>\n",
       "      <td>3008425973</td>\n",
       "      <td>A Simulation Model Demonstrating the Impact of...</td>\n",
       "      <td>In addition to seamless connectivity and smart...</td>\n",
       "      <td>2020</td>\n",
       "      <td>0</td>\n",
       "      <td>[3008013535]</td>\n",
       "      <td>[1969595988, 2024456547, 2106660896, 240927666...</td>\n",
       "      <td>[social objects, computer science, cooperative...</td>\n",
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       "    <tr>\n",
       "      <th>964346</th>\n",
       "      <td>3008480875</td>\n",
       "      <td>Scaling Blockchains to Support Electronic Heal...</td>\n",
       "      <td>Electronic Health Records (EHRs) have improved...</td>\n",
       "      <td>2020</td>\n",
       "      <td>2</td>\n",
       "      <td>[3000482756, 2560842277, 2096420846]</td>\n",
       "      <td>[1593596963, 2038708100, 2071551483, 216457208...</td>\n",
       "      <td>[health care, architecture, computer science, ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>964347</th>\n",
       "      <td>3008559546</td>\n",
       "      <td>How Good Is a Strategy in a Game with Nature</td>\n",
       "      <td>We consider games with two antagonistic player...</td>\n",
       "      <td>2020</td>\n",
       "      <td>7</td>\n",
       "      <td>[2083017933, 2033699461]</td>\n",
       "      <td>[157185084, 744920664, 1502459210, 1513485037,...</td>\n",
       "      <td>[discrete mathematics, graph, infinite game, d...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>964348</th>\n",
       "      <td>3008721399</td>\n",
       "      <td>Chunking in Soar: The Anatomy of a General Lea...</td>\n",
       "      <td>In this article we describe an approach to the...</td>\n",
       "      <td>1986</td>\n",
       "      <td>0</td>\n",
       "      <td>[2098086841, 237745248, 2126658068]</td>\n",
       "      <td>[10646503, 38913427, 86408651, 152570004, 1597...</td>\n",
       "      <td>[anatomy, architecture, chunking (psychology),...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>964349</th>\n",
       "      <td>3008773848</td>\n",
       "      <td>Shorter identifier names take longer to compre...</td>\n",
       "      <td>Developers spend the majority of their time co...</td>\n",
       "      <td>2017</td>\n",
       "      <td>4</td>\n",
       "      <td>[2576839772, 2145688174, 2166709612]</td>\n",
       "      <td>[1490674333, 1842503650, 1967931023, 203468809...</td>\n",
       "      <td>[identifier, computer science, artificial inte...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                id                                              title  \\\n",
       "964345  3008425973  A Simulation Model Demonstrating the Impact of...   \n",
       "964346  3008480875  Scaling Blockchains to Support Electronic Heal...   \n",
       "964347  3008559546       How Good Is a Strategy in a Game with Nature   \n",
       "964348  3008721399  Chunking in Soar: The Anatomy of a General Lea...   \n",
       "964349  3008773848  Shorter identifier names take longer to compre...   \n",
       "\n",
       "                                                 abstract  year  label  \\\n",
       "964345  In addition to seamless connectivity and smart...  2020      0   \n",
       "964346  Electronic Health Records (EHRs) have improved...  2020      2   \n",
       "964347  We consider games with two antagonistic player...  2020      7   \n",
       "964348  In this article we describe an approach to the...  1986      0   \n",
       "964349  Developers spend the majority of their time co...  2017      4   \n",
       "\n",
       "                                     authors  \\\n",
       "964345                          [3008013535]   \n",
       "964346  [3000482756, 2560842277, 2096420846]   \n",
       "964347              [2083017933, 2033699461]   \n",
       "964348   [2098086841, 237745248, 2126658068]   \n",
       "964349  [2576839772, 2145688174, 2166709612]   \n",
       "\n",
       "                                               references  \\\n",
       "964345  [1969595988, 2024456547, 2106660896, 240927666...   \n",
       "964346  [1593596963, 2038708100, 2071551483, 216457208...   \n",
       "964347  [157185084, 744920664, 1502459210, 1513485037,...   \n",
       "964348  [10646503, 38913427, 86408651, 152570004, 1597...   \n",
       "964349  [1490674333, 1842503650, 1967931023, 203468809...   \n",
       "\n",
       "                                                      fos  \n",
       "964345  [social objects, computer science, cooperative...  \n",
       "964346  [health care, architecture, computer science, ...  \n",
       "964347  [discrete mathematics, graph, infinite game, d...  \n",
       "964348  [anatomy, architecture, chunking (psychology),...  \n",
       "964349  [identifier, computer science, artificial inte...  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Reorder papers\n",
    "\n",
    "papers.set_index('id', inplace=True)\n",
    "papers = papers.loc[paper_id_encoder.classes_]\n",
    "papers.reset_index(inplace=True)\n",
    "papers.tail()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "316ae0b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "paper_years = papers['year'].values.astype(np.int16)\n",
    "data['paper_years'] = paper_years"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "64536f16",
   "metadata": {},
   "outputs": [],
   "source": [
    "paper_labels = papers['label'].values.astype(np.int8)\n",
    "data['paper_labels'] = paper_labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "e0333a3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'paper-paper': (array([    0,     0,     0, ..., 16345,   732,  7251], dtype=int32),\n",
       "  array([13858, 61018, 81249, ..., 19830,   744, 19890], dtype=int32)),\n",
       " 'paper-author': (array([    0,     0,     0, ..., 19890, 19890, 19882], dtype=int32),\n",
       "  array([ 10439, 196586, 212053, ..., 685977, 455354, 510243], dtype=int32)),\n",
       " 'paper-fos': (array([    0,     0,     0, ..., 19882, 19882, 19882], dtype=int32),\n",
       "  array([65253, 10791, 33819, ..., 43792,  2953, 38524], dtype=int32)),\n",
       " 'paper_years': array([2008, 2013, 2008, ..., 2020, 1986, 2017], dtype=int16),\n",
       " 'paper_labels': array([4, 6, 0, ..., 7, 0, 4], dtype=int8)}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "fce3faf6",
   "metadata": {},
   "outputs": [],
   "source": [
    "papers.to_csv('DBLP.csv', index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "32d3dd5f",
   "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 abstract 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": 20,
   "id": "1b3b9b1d",
   "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": 20,
     "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": 21,
   "id": "346dc6fa",
   "metadata": {},
   "outputs": [],
   "source": [
    "text = papers['title'] + ' ' + papers['abstract']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "cfcef3f2",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Batches: 100%|██████████| 236/236 [12:22<00:00,  3.15s/it]\n"
     ]
    }
   ],
   "source": [
    "feats = model.encode(text, batch_size=4096, show_progress_bar=True, convert_to_numpy=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ba74f1f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'paper-paper': (array([    0,     0,     0, ..., 16345,   732,  7251], dtype=int32),\n",
       "  array([13858, 61018, 81249, ..., 19830,   744, 19890], dtype=int32)),\n",
       " 'paper-author': (array([    0,     0,     0, ..., 19890, 19890, 19882], dtype=int32),\n",
       "  array([ 10439, 196586, 212053, ..., 685977, 455354, 510243], dtype=int32)),\n",
       " 'paper-fos': (array([    0,     0,     0, ..., 19882, 19882, 19882], dtype=int32),\n",
       "  array([65253, 10791, 33819, ..., 43792,  2953, 38524], dtype=int32)),\n",
       " 'paper_years': array([2008, 2013, 2008, ..., 2020, 1986, 2017], dtype=int16),\n",
       " 'paper_labels': array([4, 6, 0, ..., 7, 0, 4], dtype=int8),\n",
       " 'paper_feats': array([[-0.09045218, -0.04914903, -0.00183934, ..., -0.02621997,\n",
       "          0.10682236,  0.03757928],\n",
       "        [ 0.05457439, -0.03537758, -0.00981656, ...,  0.02816821,\n",
       "         -0.08244677,  0.05598091],\n",
       "        [ 0.05163385, -0.00435178,  0.00543169, ...,  0.04312224,\n",
       "         -0.08650234,  0.02618632],\n",
       "        ...,\n",
       "        [ 0.00644145, -0.02942889, -0.03935754, ...,  0.00694911,\n",
       "          0.04468951, -0.01565437],\n",
       "        [-0.00039966,  0.06023127, -0.01369713, ...,  0.05656872,\n",
       "         -0.0026328 ,  0.03119653],\n",
       "        [-0.02327097,  0.01399295,  0.02802348, ...,  0.07121975,\n",
       "          0.03597061, -0.01132829]], dtype=float32)}"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['paper_feats'] = feats\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "6a123fee",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "with open('dblp.pkl', 'wb') as f:\n",
    "    pickle.dump(data, f)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
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  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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 },
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