{
  "id": 420697,
  "title": "Arxiv Metadata Analysis",
  "url": "/competitions/2023-kaggle-ai-report/discussion/420697",
  "author_name": "",
  "post_date": "2023-07-02T05:07:14.510026900Z",
  "votes": 2,
  "comment_count": 2,
  "views": 0,
  "content": "<p>I published simple a notebook (work in progress) which analyses Arxiv metadata.<br>\nSo far, it extract embeddings from paper titles and clusters them.</p>\n<p><a href=\"https://www.kaggle.com/code/wagnerikeda/arxiv-metadata-analysis\" target=\"_blank\">https://www.kaggle.com/code/wagnerikeda/arxiv-metadata-analysis</a></p>",
  "messages": [
    {
      "id": "2326367",
      "postDate": "07/02/2023 05:07:14",
      "content": "<p>I published simple a notebook (work in progress) which analyses Arxiv metadata.<br>\nSo far, it extract embeddings from paper titles and clusters them.</p>\n<p><a href=\"https://www.kaggle.com/code/wagnerikeda/arxiv-metadata-analysis\" target=\"_blank\">https://www.kaggle.com/code/wagnerikeda/arxiv-metadata-analysis</a></p>",
      "rawMarkdown": "I published simple a notebook (work in progress) which analyses Arxiv metadata.\nSo far, it extract embeddings from paper titles and clusters them.\n\nhttps://www.kaggle.com/code/wagnerikeda/arxiv-metadata-analysis",
      "votes": null
    },
    {
      "id": "2385927",
      "postDate": "08/11/2023 16:26:54",
      "content": "<p>Good work Ikeda , you are in the right way !!! count on me if necessary </p>",
      "rawMarkdown": "Good work Ikeda , you are in the right way !!! count on me if necessary",
      "votes": null
    },
    {
      "id": "2385949",
      "postDate": "08/11/2023 16:42:34",
      "content": "<p>Thanks Ricardo!<br>\n3</p>",
      "rawMarkdown": "Thanks Ricardo!\n3",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 2385927,
      "author_name": "ricardomoretto",
      "author_url": "",
      "post_date": "08/11/2023 16:26:54",
      "content": "<p>Good work Ikeda , you are in the right way !!! count on me if necessary </p>",
      "votes": null,
      "replies": [
        {
          "id": 2385949,
          "author_name": "wagnerikeda",
          "author_url": "",
          "post_date": "08/11/2023 16:42:34",
          "content": "<p>Thanks Ricardo!<br>\n3</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "2326367": "I published simple a notebook (work in progress) which analyses Arxiv metadata.\nSo far, it extract embeddings from paper titles and clusters them.\n\nhttps://www.kaggle.com/code/wagnerikeda/arxiv-metadata-analysis",
    "2385927": "Good work Ikeda , you are in the right way !!! count on me if necessary",
    "2385949": "Thanks Ricardo!\n3"
  },
  "source": "meta"
}