{
  "id": 252683,
  "title": "user_portrait and item_vec",
  "url": "/competitions/bigdata2021-rl-recsys/discussion/252683",
  "author_name": "",
  "post_date": "2021-07-13T12:17:15.888816100Z",
  "votes": 3,
  "comment_count": 3,
  "views": 0,
  "content": "<p>user_portrait: \"64054,35323,6599,36504,24180,37350,83978,21927,74820,2517\"<br>\nitem_vec: \"2,2,1,0.015764\"</p>\n<p>Does the scale of the features meaningful?<br>\nShould we treat them as continuous values (e.g. 1 for 1 yrs old, 2 for 2 yrs old, 3 for 3yrs old)?<br>\nOr should we treat them as discrete ones (e.g. 1 for boy, 2 for girl, 3 for married, 4 for chinese, 5 for korean, 6 for japanese) ?</p>",
  "messages": [
    {
      "id": "1386332",
      "postDate": "07/13/2021 12:17:15",
      "content": "<p>user_portrait: \"64054,35323,6599,36504,24180,37350,83978,21927,74820,2517\"<br>\nitem_vec: \"2,2,1,0.015764\"</p>\n<p>Does the scale of the features meaningful?<br>\nShould we treat them as continuous values (e.g. 1 for 1 yrs old, 2 for 2 yrs old, 3 for 3yrs old)?<br>\nOr should we treat them as discrete ones (e.g. 1 for boy, 2 for girl, 3 for married, 4 for chinese, 5 for korean, 6 for japanese) ?</p>",
      "rawMarkdown": "user_portrait: \"64054,35323,6599,36504,24180,37350,83978,21927,74820,2517\"\nitem_vec: \"2,2,1,0.015764\"\n\nDoes the scale of the features meaningful?\nShould we treat them as continuous values (e.g. 1 for 1 yrs old, 2 for 2 yrs old, 3 for 3yrs old)?\nOr should we treat them as discrete ones (e.g. 1 for boy, 2 for girl, 3 for married, 4 for chinese, 5 for korean, 6 for japanese) ?",
      "votes": null
    },
    {
      "id": "1386612",
      "postDate": "07/13/2021 15:21:40",
      "content": "<p>There are several outliers in the fourth number of item_vec.<br>\nfor most items, it's something like 0.015764<br>\nHowever, <br>\nfor 70th item, it's 7.556912,<br>\nfor 95th item, it's 8.385067,<br>\nfor 96th item, it's 9.316741.</p>\n<p>Just confirming, is this correct? or is this a mistake?</p>",
      "rawMarkdown": "There are several outliers in the fourth number of item_vec.\nfor most items, it's something like 0.015764\nHowever, \nfor 70th item, it's 7.556912,\nfor 95th item, it's 8.385067,\nfor 96th item, it's 9.316741.\n\nJust confirming, is this correct? or is this a mistake?",
      "votes": null
    },
    {
      "id": "1387589",
      "postDate": "07/14/2021 09:41:48",
      "content": "<p>Discrete features except for 0.015764.</p>",
      "rawMarkdown": "Discrete features except for 0.015764.",
      "votes": null
    },
    {
      "id": "1387590",
      "postDate": "07/14/2021 09:42:39",
      "content": "<p>Correct.     </p>",
      "rawMarkdown": "Correct.",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1386612,
      "author_name": "lzhbrian",
      "author_url": "",
      "post_date": "07/13/2021 15:21:40",
      "content": "<p>There are several outliers in the fourth number of item_vec.<br>\nfor most items, it's something like 0.015764<br>\nHowever, <br>\nfor 70th item, it's 7.556912,<br>\nfor 95th item, it's 8.385067,<br>\nfor 96th item, it's 9.316741.</p>\n<p>Just confirming, is this correct? or is this a mistake?</p>",
      "votes": null,
      "replies": [
        {
          "id": 1387590,
          "author_name": "sword10086",
          "author_url": "",
          "post_date": "07/14/2021 09:42:39",
          "content": "<p>Correct.     </p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 1387589,
      "author_name": "sword10086",
      "author_url": "",
      "post_date": "07/14/2021 09:41:48",
      "content": "<p>Discrete features except for 0.015764.</p>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1386332": "user_portrait: \"64054,35323,6599,36504,24180,37350,83978,21927,74820,2517\"\nitem_vec: \"2,2,1,0.015764\"\n\nDoes the scale of the features meaningful?\nShould we treat them as continuous values (e.g. 1 for 1 yrs old, 2 for 2 yrs old, 3 for 3yrs old)?\nOr should we treat them as discrete ones (e.g. 1 for boy, 2 for girl, 3 for married, 4 for chinese, 5 for korean, 6 for japanese) ?",
    "1386612": "There are several outliers in the fourth number of item_vec.\nfor most items, it's something like 0.015764\nHowever, \nfor 70th item, it's 7.556912,\nfor 95th item, it's 8.385067,\nfor 96th item, it's 9.316741.\n\nJust confirming, is this correct? or is this a mistake?",
    "1387589": "Discrete features except for 0.015764.",
    "1387590": "Correct."
  },
  "source": "meta"
}