diff --git a/examples/Sort_Google_Scholar_No_Code_Version.ipynb b/examples/Sort_Google_Scholar_No_Code_Version.ipynb
index c098247..8ac1f23 100644
--- a/examples/Sort_Google_Scholar_No_Code_Version.ipynb
+++ b/examples/Sort_Google_Scholar_No_Code_Version.ipynb
@@ -19,7 +19,7 @@
         "colab_type": "text"
       },
       "source": [
-        "<a href=\"https://colab.research.google.com/github/WittmannF/sort-google-scholar/blob/no_code_nb/examples/Sort_Google_Scholar_No_Code_Version.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+        "<a href=\"https://colab.research.google.com/github/WittmannF/sort-google-scholar/blob/master/examples/Sort_Google_Scholar_No_Code_Version.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
     {
@@ -39,13 +39,13 @@
     {
       "cell_type": "code",
       "source": [
-        "search_query = \"large language models\" # @param {type:\"string\"}"
+        "search_query = \"machine learning\" # @param {type:\"string\"}"
       ],
       "metadata": {
         "cellView": "form",
         "id": "xlpCibrIV4Nk"
       },
-      "execution_count": null,
+      "execution_count": 1,
       "outputs": []
     },
     {
@@ -83,6 +83,13 @@
         "nresults = 100  # @param {type:\"number\"}\n",
         "startyear = None  # @param {type:\"string\"}\n",
         "endyear = None  # @param {type:\"string\"}\n",
+        "langfilter = None  # @param [\"None\", \"zh-CN\", \"zh-TW\", \"nl\", \"en\", \"fr\", \"de\", \"it\", \"ja\", \"ko\", \"pl\", \"pt\", \"es\", \"tr\"] {type:\"string\"}\n",
+        "\n",
+        "# Convert the langfilter to a list if it's not None\n",
+        "if langfilter and langfilter != \"None\":\n",
+        "    langfilter = [langfilter]\n",
+        "else:\n",
+        "    langfilter = None  # No language filter applied if \"None\" is selected\n",
         "\n",
         "# Constructing the base command\n",
         "cmd = f\"sortgs '{search_query}' --sortby '{sortby}' --nresults {nresults}\"\n",
@@ -93,14 +100,31 @@
         "if endyear:\n",
         "    cmd += f\" --endyear {endyear}\"\n",
         "\n",
-        "\n"
+        "if langfilter:\n",
+        "    lang_str = ' '.join(langfilter)\n",
+        "    cmd += f\" --langfilter {lang_str}\"\n",
+        "\n",
+        "# Output the constructed command for review\n",
+        "print(\"Constructed command:\", cmd)\n"
       ],
       "metadata": {
         "cellView": "form",
-        "id": "VbVaoz3wYGQY"
+        "id": "VbVaoz3wYGQY",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "9de8ff16-0bd0-468e-a28d-20f0dbc5973b"
       },
-      "execution_count": null,
-      "outputs": []
+      "execution_count": 2,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Constructed command: sortgs 'machine learning' --sortby 'cit/year' --nresults 100\n"
+          ]
+        }
+      ]
     },
     {
       "cell_type": "markdown",
@@ -115,14 +139,29 @@
       "cell_type": "code",
       "metadata": {
         "id": "oPot8aWcsfei",
-        "cellView": "form"
+        "cellView": "form",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "6c37c6ae-fcba-4a55-9759-997ed004f991"
       },
       "source": [
         "# @title\n",
         "!pip install sortgs --quiet"
       ],
-      "execution_count": null,
-      "outputs": []
+      "execution_count": 3,
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.7/9.7 MB\u001b[0m \u001b[31m40.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m476.0/476.0 kB\u001b[0m \u001b[31m8.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m58.3/58.3 kB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h"
+          ]
+        }
+      ]
     },
     {
       "cell_type": "code",
@@ -136,16 +175,16 @@
         },
         "cellView": "form",
         "id": "qgfQT7i2XrPf",
-        "outputId": "a3ea8b37-154f-420e-95df-72471e0a53c0"
+        "outputId": "c9adeaee-74b3-4b8d-fbd7-6127d9e5f229"
       },
-      "execution_count": null,
+      "execution_count": 4,
       "outputs": [
         {
           "output_type": "stream",
           "name": "stdout",
           "text": [
             "Running with the following parameters:\n",
-            "Keyword: large language models, Number of results: 100, Save database: True, Path: /content, Sort by: cit/year, Plot results: False, Start year: None, End year: 2024, Debug: False\n",
+            "Keyword: machine learning, Number of results: 100, Save database: True, Path: /content, Sort by: cit/year, Plot results: False, Start year: None, End year: 2024, Debug: False\n",
             "Loading next 10 results\n",
             "Loading next 20 results\n",
             "Loading next 30 results\n",
@@ -156,22 +195,22 @@
             "Loading next 80 results\n",
             "Loading next 90 results\n",
             "Loading next 100 results\n",
-            "                                             Author  ... cit/year\n",
-            "Rank                                                 ...         \n",
-            "57                       Wei, X Wang, D Schuurmans…  ...     2406\n",
-            "80                     Hu, Y Shen, P Wallis, Z Alle  ...     1652\n",
-            "1        Kasneci, K Seßler, S Küchemann, M Bannert…  ...     1390\n",
-            "78                    Yao, D Yu, J Zhao, I Shafran…  ...     1304\n",
-            "3              Chang, X Wang, J Wang, Y Wu, L Yang…  ...     1198\n",
-            "...                                             ...  ...      ...\n",
-            "84                     Maatouk, N Piovesan, F Ayed…  ...       29\n",
-            "45    Li, L Xia, J Tang, Y Xu, L Shi, L Xia, D Yin…  ...       23\n",
-            "82                            Cheng, S Huang, F Wei  ...       22\n",
-            "50               Zhu, Q Zhao, H Chen, J Wang, X Xie  ...       14\n",
-            "73            Ren, J Tang, D Yin, N Chawla, C Huang  ...        6\n",
+            "                                     Author  ... cit/year\n",
+            "Rank                                         ...         \n",
+            "93                     Bishop, NM Nasrabadi  ...     3911\n",
+            "22                                 Alpaydin  ...     2936\n",
+            "19                    Mitchell, TM Mitchell  ...     1404\n",
+            "30                                   Murphy  ...     1273\n",
+            "3                       Jordan, TM Mitchell  ...      958\n",
+            "...                                     ...  ...      ...\n",
+            "59              Singh, PK Bhatia, O Sangwan  ...       10\n",
+            "7                                Dietterich  ...        7\n",
+            "35            Kubat, I Bratko, RS Michalski  ...        5\n",
+            "44     Carbonell, RS Michalski, TM Mitchell  ...        4\n",
+            "52                                   Burkov  ...        1\n",
             "\n",
             "[100 rows x 8 columns]\n",
-            "Results saved to /content/large_language_models.csv\n"
+            "Results saved to /content/machine_learning.csv\n"
           ]
         }
       ]
@@ -222,9 +261,9 @@
         "id": "pM_Bb4MH14eI",
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 2951
+          "height": 563
         },
-        "outputId": "8cb7847d-28b4-47cd-ad16-21f20e72b745",
+        "outputId": "b3eaf306-feb9-4306-e32f-726e5808c640",
         "cellView": "form"
       },
       "source": [
@@ -233,69 +272,69 @@
         "results = pd.read_csv(search_query.replace(' ', '_')+'.csv')\n",
         "results"
       ],
-      "execution_count": null,
+      "execution_count": 5,
       "outputs": [
         {
           "output_type": "execute_result",
           "data": {
             "text/plain": [
-              "    Rank                                         Author  \\\n",
-              "0     57                     Wei, X Wang, D Schuurmans…   \n",
-              "1     80                   Hu, Y Shen, P Wallis, Z Alle   \n",
-              "2      1     Kasneci, K Seßler, S Küchemann, M Bannert…   \n",
-              "3     78                  Yao, D Yu, J Zhao, I Shafran…   \n",
-              "4      3           Chang, X Wang, J Wang, Y Wu, L Yang…   \n",
-              "..   ...                                            ...   \n",
-              "95    84                   Maatouk, N Piovesan, F Ayed…   \n",
-              "96    45  Li, L Xia, J Tang, Y Xu, L Shi, L Xia, D Yin…   \n",
-              "97    82                          Cheng, S Huang, F Wei   \n",
-              "98    50             Zhu, Q Zhao, H Chen, J Wang, X Xie   \n",
-              "99    73          Ren, J Tang, D Yin, N Chawla, C Huang   \n",
+              "    Rank                                 Author  \\\n",
+              "0     93                   Bishop, NM Nasrabadi   \n",
+              "1     22                               Alpaydin   \n",
+              "2     19                  Mitchell, TM Mitchell   \n",
+              "3     30                                 Murphy   \n",
+              "4      3                    Jordan, TM Mitchell   \n",
+              "..   ...                                    ...   \n",
+              "95    59            Singh, PK Bhatia, O Sangwan   \n",
+              "96     7                             Dietterich   \n",
+              "97    35          Kubat, I Bratko, RS Michalski   \n",
+              "98    44   Carbonell, RS Michalski, TM Mitchell   \n",
+              "99    52                                 Burkov   \n",
               "\n",
               "                                                Title  Citations  Year  \\\n",
-              "0   Chain-of-thought prompting elicits reasoning i...       7219  2022   \n",
-              "1   Lora: Low-rank adaptation of large language mo...       6608  2021   \n",
-              "2   ChatGPT for good? On opportunities and challen...       2779  2023   \n",
-              "3   Tree of thoughts: Deliberate problem solving w...       1304  2024   \n",
-              "4     A survey on evaluation of large language models       1198  2024   \n",
+              "0            Pattern recognition and machine learning      74300  2006   \n",
+              "1                    Introduction to machine learning      14680  2020   \n",
+              "2                                    Machine learning      39313  1997   \n",
+              "3       Machine learning: a probabilistic perspective      16548  2012   \n",
+              "4   Machine learning: Trends, perspectives, and pr...       9579  2015   \n",
               "..                                                ...        ...   ...   \n",
-              "95  Large language models for telecom: Forthcoming...         29  2024   \n",
-              "96    Urbangpt: Spatio-temporal large language models         23  2024   \n",
-              "97  Adapting large language models via reading com...         44  2023   \n",
-              "98  Promptbench: A unified library for evaluation ...         14  2024   \n",
-              "99       A survey of large language models for graphs          6  2024   \n",
-              "\n",
-              "                  Publisher                                       Venue  \\\n",
-              "0    proceedings.neurips.cc                        Advances in neural …   \n",
-              "1                 arxiv.org                      arXiv preprint arXiv …   \n",
-              "2                  Elsevier                   Learning and individual …   \n",
-              "3    proceedings.neurips.cc                               Advances in …   \n",
-              "4                dl.acm.org                       ACM Transactions on …   \n",
-              "..                      ...                                         ...   \n",
-              "95      ieeexplore.ieee.org                                      IEEE …   \n",
-              "96               dl.acm.org                   Proceedings of the 30th …   \n",
-              "97           openreview.net   The Twelfth International Conference on …   \n",
-              "98                 jmlr.org               Journal of Machine Learning …   \n",
-              "99               dl.acm.org                   Proceedings of the 30th …   \n",
+              "95  A review of studies on machine learning techni...        180  2007   \n",
+              "96                                   Machine learning        260  1990   \n",
+              "97               A review of machine learning methods        123  1998   \n",
+              "98  Machine learning: A historical and methodologi...        149  1983   \n",
+              "99             The hundred-page machine learning book       1085     0   \n",
+              "\n",
+              "            Publisher                                Venue  \\\n",
+              "0            Springer                                  NaN   \n",
+              "1    books.google.com                                  NaN   \n",
+              "2        pachecoj.com                                  NaN   \n",
+              "3    books.google.com                                  NaN   \n",
+              "4         science.org                              Science   \n",
+              "..                ...                                  ...   \n",
+              "95   books.google.com           International Journal of …   \n",
+              "96           Citeseer    Annual review of computer science   \n",
+              "97           Citeseer   Machine learning and data mining …   \n",
+              "98       ojs.aaai.org                          AI Magazine   \n",
+              "99         papers.com                                  NaN   \n",
               "\n",
               "                                               Source  cit/year  \n",
-              "0   https://proceedings.neurips.cc/paper_files/pap...      2406  \n",
-              "1                    https://arxiv.org/abs/2106.09685      1652  \n",
-              "2   https://www.sciencedirect.com/science/article/...      1390  \n",
-              "3   https://proceedings.neurips.cc/paper_files/pap...      1304  \n",
-              "4          https://dl.acm.org/doi/abs/10.1145/3641289      1198  \n",
+              "0        https://link.springer.com/book/9780387310732      3911  \n",
+              "1   https://books.google.com/books?hl=en&lr=&id=tZ...      2936  \n",
+              "2   http://www.pachecoj.com/courses/csc380_fall21/...      1404  \n",
+              "3   https://books.google.com/books?hl=en&lr=&id=RC...      1273  \n",
+              "4   https://www.science.org/doi/abs/10.1126/scienc...       958  \n",
               "..                                                ...       ...  \n",
-              "95  https://ieeexplore.ieee.org/abstract/document/...        29  \n",
-              "96  https://dl.acm.org/doi/abs/10.1145/3637528.367...        23  \n",
-              "97         https://openreview.net/forum?id=y886UXPEZ0        22  \n",
-              "98       https://www.jmlr.org/papers/v25/24-0023.html        14  \n",
-              "99  https://dl.acm.org/doi/abs/10.1145/3637528.367...         6  \n",
+              "95  https://books.google.com/books?hl=en&lr=&id=7x...        10  \n",
+              "96  https://citeseerx.ist.psu.edu/document?repid=r...         7  \n",
+              "97  https://citeseerx.ist.psu.edu/document?repid=r...         5  \n",
+              "98  https://ojs.aaai.org/aimagazine/index.php/aima...         4  \n",
+              "99  https://order-papers.com/sites/default/files/t...         1  \n",
               "\n",
               "[100 rows x 9 columns]"
             ],
             "text/html": [
               "\n",
-              "  <div id=\"df-d2f70cf2-8fdd-469c-b4c8-d648e60e9554\" class=\"colab-df-container\">\n",
+              "  <div id=\"df-668fd144-8d7d-487f-8424-b1a6dde6c89f\" class=\"colab-df-container\">\n",
               "    <div>\n",
               "<style scoped>\n",
               "    .dataframe tbody tr th:only-of-type {\n",
@@ -328,63 +367,63 @@
               "  <tbody>\n",
               "    <tr>\n",
               "      <th>0</th>\n",
-              "      <td>57</td>\n",
-              "      <td>Wei, X Wang, D Schuurmans…</td>\n",
-              "      <td>Chain-of-thought prompting elicits reasoning i...</td>\n",
-              "      <td>7219</td>\n",
-              "      <td>2022</td>\n",
-              "      <td>proceedings.neurips.cc</td>\n",
-              "      <td>Advances in neural …</td>\n",
-              "      <td>https://proceedings.neurips.cc/paper_files/pap...</td>\n",
-              "      <td>2406</td>\n",
+              "      <td>93</td>\n",
+              "      <td>Bishop, NM Nasrabadi</td>\n",
+              "      <td>Pattern recognition and machine learning</td>\n",
+              "      <td>74300</td>\n",
+              "      <td>2006</td>\n",
+              "      <td>Springer</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>https://link.springer.com/book/9780387310732</td>\n",
+              "      <td>3911</td>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>1</th>\n",
-              "      <td>80</td>\n",
-              "      <td>Hu, Y Shen, P Wallis, Z Alle</td>\n",
-              "      <td>Lora: Low-rank adaptation of large language mo...</td>\n",
-              "      <td>6608</td>\n",
-              "      <td>2021</td>\n",
-              "      <td>arxiv.org</td>\n",
-              "      <td>arXiv preprint arXiv …</td>\n",
-              "      <td>https://arxiv.org/abs/2106.09685</td>\n",
-              "      <td>1652</td>\n",
+              "      <td>22</td>\n",
+              "      <td>Alpaydin</td>\n",
+              "      <td>Introduction to machine learning</td>\n",
+              "      <td>14680</td>\n",
+              "      <td>2020</td>\n",
+              "      <td>books.google.com</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>https://books.google.com/books?hl=en&amp;lr=&amp;id=tZ...</td>\n",
+              "      <td>2936</td>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>2</th>\n",
-              "      <td>1</td>\n",
-              "      <td>Kasneci, K Seßler, S Küchemann, M Bannert…</td>\n",
-              "      <td>ChatGPT for good? On opportunities and challen...</td>\n",
-              "      <td>2779</td>\n",
-              "      <td>2023</td>\n",
-              "      <td>Elsevier</td>\n",
-              "      <td>Learning and individual …</td>\n",
-              "      <td>https://www.sciencedirect.com/science/article/...</td>\n",
-              "      <td>1390</td>\n",
+              "      <td>19</td>\n",
+              "      <td>Mitchell, TM Mitchell</td>\n",
+              "      <td>Machine learning</td>\n",
+              "      <td>39313</td>\n",
+              "      <td>1997</td>\n",
+              "      <td>pachecoj.com</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>http://www.pachecoj.com/courses/csc380_fall21/...</td>\n",
+              "      <td>1404</td>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>3</th>\n",
-              "      <td>78</td>\n",
-              "      <td>Yao, D Yu, J Zhao, I Shafran…</td>\n",
-              "      <td>Tree of thoughts: Deliberate problem solving w...</td>\n",
-              "      <td>1304</td>\n",
-              "      <td>2024</td>\n",
-              "      <td>proceedings.neurips.cc</td>\n",
-              "      <td>Advances in …</td>\n",
-              "      <td>https://proceedings.neurips.cc/paper_files/pap...</td>\n",
-              "      <td>1304</td>\n",
+              "      <td>30</td>\n",
+              "      <td>Murphy</td>\n",
+              "      <td>Machine learning: a probabilistic perspective</td>\n",
+              "      <td>16548</td>\n",
+              "      <td>2012</td>\n",
+              "      <td>books.google.com</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>https://books.google.com/books?hl=en&amp;lr=&amp;id=RC...</td>\n",
+              "      <td>1273</td>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>4</th>\n",
               "      <td>3</td>\n",
-              "      <td>Chang, X Wang, J Wang, Y Wu, L Yang…</td>\n",
-              "      <td>A survey on evaluation of large language models</td>\n",
-              "      <td>1198</td>\n",
-              "      <td>2024</td>\n",
-              "      <td>dl.acm.org</td>\n",
-              "      <td>ACM Transactions on …</td>\n",
-              "      <td>https://dl.acm.org/doi/abs/10.1145/3641289</td>\n",
-              "      <td>1198</td>\n",
+              "      <td>Jordan, TM Mitchell</td>\n",
+              "      <td>Machine learning: Trends, perspectives, and pr...</td>\n",
+              "      <td>9579</td>\n",
+              "      <td>2015</td>\n",
+              "      <td>science.org</td>\n",
+              "      <td>Science</td>\n",
+              "      <td>https://www.science.org/doi/abs/10.1126/scienc...</td>\n",
+              "      <td>958</td>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>...</th>\n",
@@ -400,63 +439,63 @@
               "    </tr>\n",
               "    <tr>\n",
               "      <th>95</th>\n",
-              "      <td>84</td>\n",
-              "      <td>Maatouk, N Piovesan, F Ayed…</td>\n",
-              "      <td>Large language models for telecom: Forthcoming...</td>\n",
-              "      <td>29</td>\n",
-              "      <td>2024</td>\n",
-              "      <td>ieeexplore.ieee.org</td>\n",
-              "      <td>IEEE …</td>\n",
-              "      <td>https://ieeexplore.ieee.org/abstract/document/...</td>\n",
-              "      <td>29</td>\n",
+              "      <td>59</td>\n",
+              "      <td>Singh, PK Bhatia, O Sangwan</td>\n",
+              "      <td>A review of studies on machine learning techni...</td>\n",
+              "      <td>180</td>\n",
+              "      <td>2007</td>\n",
+              "      <td>books.google.com</td>\n",
+              "      <td>International Journal of …</td>\n",
+              "      <td>https://books.google.com/books?hl=en&amp;lr=&amp;id=7x...</td>\n",
+              "      <td>10</td>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>96</th>\n",
-              "      <td>45</td>\n",
-              "      <td>Li, L Xia, J Tang, Y Xu, L Shi, L Xia, D Yin…</td>\n",
-              "      <td>Urbangpt: Spatio-temporal large language models</td>\n",
-              "      <td>23</td>\n",
-              "      <td>2024</td>\n",
-              "      <td>dl.acm.org</td>\n",
-              "      <td>Proceedings of the 30th …</td>\n",
-              "      <td>https://dl.acm.org/doi/abs/10.1145/3637528.367...</td>\n",
-              "      <td>23</td>\n",
+              "      <td>7</td>\n",
+              "      <td>Dietterich</td>\n",
+              "      <td>Machine learning</td>\n",
+              "      <td>260</td>\n",
+              "      <td>1990</td>\n",
+              "      <td>Citeseer</td>\n",
+              "      <td>Annual review of computer science</td>\n",
+              "      <td>https://citeseerx.ist.psu.edu/document?repid=r...</td>\n",
+              "      <td>7</td>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>97</th>\n",
-              "      <td>82</td>\n",
-              "      <td>Cheng, S Huang, F Wei</td>\n",
-              "      <td>Adapting large language models via reading com...</td>\n",
-              "      <td>44</td>\n",
-              "      <td>2023</td>\n",
-              "      <td>openreview.net</td>\n",
-              "      <td>The Twelfth International Conference on …</td>\n",
-              "      <td>https://openreview.net/forum?id=y886UXPEZ0</td>\n",
-              "      <td>22</td>\n",
+              "      <td>35</td>\n",
+              "      <td>Kubat, I Bratko, RS Michalski</td>\n",
+              "      <td>A review of machine learning methods</td>\n",
+              "      <td>123</td>\n",
+              "      <td>1998</td>\n",
+              "      <td>Citeseer</td>\n",
+              "      <td>Machine learning and data mining …</td>\n",
+              "      <td>https://citeseerx.ist.psu.edu/document?repid=r...</td>\n",
+              "      <td>5</td>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>98</th>\n",
-              "      <td>50</td>\n",
-              "      <td>Zhu, Q Zhao, H Chen, J Wang, X Xie</td>\n",
-              "      <td>Promptbench: A unified library for evaluation ...</td>\n",
-              "      <td>14</td>\n",
-              "      <td>2024</td>\n",
-              "      <td>jmlr.org</td>\n",
-              "      <td>Journal of Machine Learning …</td>\n",
-              "      <td>https://www.jmlr.org/papers/v25/24-0023.html</td>\n",
-              "      <td>14</td>\n",
+              "      <td>44</td>\n",
+              "      <td>Carbonell, RS Michalski, TM Mitchell</td>\n",
+              "      <td>Machine learning: A historical and methodologi...</td>\n",
+              "      <td>149</td>\n",
+              "      <td>1983</td>\n",
+              "      <td>ojs.aaai.org</td>\n",
+              "      <td>AI Magazine</td>\n",
+              "      <td>https://ojs.aaai.org/aimagazine/index.php/aima...</td>\n",
+              "      <td>4</td>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th>99</th>\n",
-              "      <td>73</td>\n",
-              "      <td>Ren, J Tang, D Yin, N Chawla, C Huang</td>\n",
-              "      <td>A survey of large language models for graphs</td>\n",
-              "      <td>6</td>\n",
-              "      <td>2024</td>\n",
-              "      <td>dl.acm.org</td>\n",
-              "      <td>Proceedings of the 30th …</td>\n",
-              "      <td>https://dl.acm.org/doi/abs/10.1145/3637528.367...</td>\n",
-              "      <td>6</td>\n",
+              "      <td>52</td>\n",
+              "      <td>Burkov</td>\n",
+              "      <td>The hundred-page machine learning book</td>\n",
+              "      <td>1085</td>\n",
+              "      <td>0</td>\n",
+              "      <td>papers.com</td>\n",
+              "      <td>NaN</td>\n",
+              "      <td>https://order-papers.com/sites/default/files/t...</td>\n",
+              "      <td>1</td>\n",
               "    </tr>\n",
               "  </tbody>\n",
               "</table>\n",
@@ -465,7 +504,7 @@
               "    <div class=\"colab-df-buttons\">\n",
               "\n",
               "  <div class=\"colab-df-container\">\n",
-              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d2f70cf2-8fdd-469c-b4c8-d648e60e9554')\"\n",
+              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-668fd144-8d7d-487f-8424-b1a6dde6c89f')\"\n",
               "            title=\"Convert this dataframe to an interactive table.\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -517,12 +556,12 @@
               "\n",
               "    <script>\n",
               "      const buttonEl =\n",
-              "        document.querySelector('#df-d2f70cf2-8fdd-469c-b4c8-d648e60e9554 button.colab-df-convert');\n",
+              "        document.querySelector('#df-668fd144-8d7d-487f-8424-b1a6dde6c89f button.colab-df-convert');\n",
               "      buttonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
               "      async function convertToInteractive(key) {\n",
-              "        const element = document.querySelector('#df-d2f70cf2-8fdd-469c-b4c8-d648e60e9554');\n",
+              "        const element = document.querySelector('#df-668fd144-8d7d-487f-8424-b1a6dde6c89f');\n",
               "        const dataTable =\n",
               "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
               "                                                    [key], {});\n",
@@ -542,8 +581,8 @@
               "  </div>\n",
               "\n",
               "\n",
-              "<div id=\"df-73499d95-ab5e-494d-bdc9-f07dde53c63b\">\n",
-              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-73499d95-ab5e-494d-bdc9-f07dde53c63b')\"\n",
+              "<div id=\"df-86269494-2cd1-4941-a3f1-6f5ff12227bc\">\n",
+              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-86269494-2cd1-4941-a3f1-6f5ff12227bc')\"\n",
               "            title=\"Suggest charts\"\n",
               "            style=\"display:none;\">\n",
               "\n",
@@ -662,14 +701,14 @@
               "    }\n",
               "    (() => {\n",
               "      let quickchartButtonEl =\n",
-              "        document.querySelector('#df-73499d95-ab5e-494d-bdc9-f07dde53c63b button');\n",
+              "        document.querySelector('#df-86269494-2cd1-4941-a3f1-6f5ff12227bc button');\n",
               "      quickchartButtonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "    })();\n",
               "  </script>\n",
               "</div>\n",
               "\n",
-              "  <div id=\"id_6b800562-1bcf-42a2-9d46-dc538342b871\">\n",
+              "  <div id=\"id_8a4436bd-b800-4c30-8497-0d5fb842f9f9\">\n",
               "    <style>\n",
               "      .colab-df-generate {\n",
               "        background-color: #E8F0FE;\n",
@@ -713,7 +752,7 @@
               "    <script>\n",
               "      (() => {\n",
               "      const buttonEl =\n",
-              "        document.querySelector('#id_6b800562-1bcf-42a2-9d46-dc538342b871 button.colab-df-generate');\n",
+              "        document.querySelector('#id_8a4436bd-b800-4c30-8497-0d5fb842f9f9 button.colab-df-generate');\n",
               "      buttonEl.style.display =\n",
               "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
               "\n",
@@ -730,11 +769,11 @@
             "application/vnd.google.colaboratory.intrinsic+json": {
               "type": "dataframe",
               "variable_name": "results",
-              "summary": "{\n  \"name\": \"results\",\n  \"rows\": 100,\n  \"fields\": [\n    {\n      \"column\": \"Rank\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 29,\n        \"min\": 1,\n        \"max\": 100,\n        \"num_unique_values\": 100,\n        \"samples\": [\n          62,\n          47,\n          51\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Author\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 100,\n        \"samples\": [\n          \"Yu, D Iter, S Wang, Y Xu, M Ju, S Sanyal\\u2026\",\n          \"Hou, Y Zhao, Y Liu, Z Yang, K Wang, L Li\\u2026\",\n          \"Ab\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 99,\n        \"samples\": [\n          \"Tidybot: Personalized robot assistance with large language models\",\n          \"Exploring the potential of large language models (llms) in learning on graphs\",\n          \"Urbangpt: Spatio-temporal large language models\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Citations\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1078,\n        \"min\": 6,\n        \"max\": 7219,\n        \"num_unique_values\": 92,\n        \"samples\": [\n          350,\n          310,\n          247\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1,\n        \"min\": 2007,\n        \"max\": 2024,\n        \"num_unique_values\": 6,\n        \"samples\": [\n          2022,\n          2021,\n          2019\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Publisher\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 21,\n        \"samples\": [\n          \" proceedings.neurips.cc\",\n          \" openreview.net\",\n          \" thelancet.com\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Venue\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 56,\n        \"samples\": [\n          \" Advances in neural\\u00a0\\u2026\",\n          \" Nature medicine\",\n          \" Authorea\\u00a0\\u2026\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Source\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 100,\n        \"samples\": [\n          \"https://arxiv.org/abs/2209.10063\",\n          \"https://dl.acm.org/doi/abs/10.1145/3695988\",\n          \"https://mededu.jmir.org/2023/1/e48291/\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cit/year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 374,\n        \"min\": 6,\n        \"max\": 2406,\n        \"num_unique_values\": 85,\n        \"samples\": [\n          42,\n          2406,\n          73\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
+              "summary": "{\n  \"name\": \"results\",\n  \"rows\": 100,\n  \"fields\": [\n    {\n      \"column\": \"Rank\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 29,\n        \"min\": 1,\n        \"max\": 100,\n        \"num_unique_values\": 100,\n        \"samples\": [\n          32,\n          83,\n          12\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Author\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 91,\n        \"samples\": [\n          \"Mohammed, MB Khan, EBM Bashier\",\n          \"Sammut, GI Webb\",\n          \"Ribeiro, K Grolinger\\u2026\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 92,\n        \"samples\": [\n          \"Machine learning: algorithms and applications\",\n          \"Encyclopedia of machine learning\",\n          \"Machine learning and its applications to biology\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Citations\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 8563,\n        \"min\": 101,\n        \"max\": 74300,\n        \"num_unique_values\": 96,\n        \"samples\": [\n          532,\n          1013,\n          207\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 201,\n        \"min\": 0,\n        \"max\": 2023,\n        \"num_unique_values\": 28,\n        \"samples\": [\n          2019,\n          1990,\n          2014\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Publisher\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 37,\n        \"samples\": [\n          \" iopscience.iop.org\",\n          \" elgaronline.com\",\n          \" dlib.hust.edu.vn\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Venue\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 56,\n        \"samples\": [\n          \" Science\",\n          \" Annual review of fluid\\u00a0\\u2026\",\n          \" Cambridge University  UK\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Source\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 100,\n        \"samples\": [\n          \"https://www.lamda.nju.edu.cn/publication/fcs16learnware.pdf\",\n          \"https://pubs.acs.org/doi/abs/10.1021/jacs.0c09105\",\n          \"https://books.google.com/books?hl=en&lr=&id=TNg5qVoqRtUC&oi=fnd&pg=PR9&dq=machine+learning&ots=Q5mtZtrYNk&sig=txCgWhcfZiDRYkNPkcE-iA4x3Uc\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"cit/year\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 535,\n        \"min\": 1,\n        \"max\": 3911,\n        \"num_unique_values\": 86,\n        \"samples\": [\n          18,\n          3911,\n          23\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
             }
           },
           "metadata": {},
-          "execution_count": 20
+          "execution_count": 5
         }
       ]
     },
@@ -780,7 +819,7 @@
         "fig.show()"
       ],
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 6,
       "outputs": [
         {
           "output_type": "display_data",
@@ -790,9 +829,9 @@
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               "<body>\n",
               "    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
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