{
  "id": 521670,
  "title": "Store Front with Recommendations Playground ",
  "url": "/competitions/h-and-m-personalized-fashion-recommendations/discussion/521670",
  "author_name": "malaccan",
  "post_date": "2024-07-22T09:49:18.461000",
  "votes": 0,
  "comment_count": 0,
  "views": 0,
  "content": "<p>we have been very impressed by the many different approaches made by this community. hence we thought we implement our version as a web playground that anyone can test (with a view to be simplistic and practical).</p>\n<p>any user can browse the listings, and add (or remove) to cart any items they like. our recommendation engine works by monitoring the contents of the shopping cart, and recommend items based on \"nearest\" shopper that fits similar shopping profiles.</p>\n<p><a href=\"https://sempoa.ai/projects/hm\" target=\"_blank\">https://sempoa.ai/projects/hm</a></p>\n<p>we wrote several blogs about it on our site, but feel free to have a play!</p>",
  "messages": [
    {
      "id": 2931742,
      "postDate": "2024-07-22T09:49:18.460Z",
      "content": "<p>we have been very impressed by the many different approaches made by this community. hence we thought we implement our version as a web playground that anyone can test (with a view to be simplistic and practical).</p>\n<p>any user can browse the listings, and add (or remove) to cart any items they like. our recommendation engine works by monitoring the contents of the shopping cart, and recommend items based on \"nearest\" shopper that fits similar shopping profiles.</p>\n<p><a href=\"https://sempoa.ai/projects/hm\" target=\"_blank\">https://sempoa.ai/projects/hm</a></p>\n<p>we wrote several blogs about it on our site, but feel free to have a play!</p>",
      "rawMarkdown": "we have been very impressed by the many different approaches made by this community. hence we thought we implement our version as a web playground that anyone can test (with a view to be simplistic and practical).\n\nany user can browse the listings, and add (or remove) to cart any items they like. our recommendation engine works by monitoring the contents of the shopping cart, and recommend items based on \"nearest\" shopper that fits similar shopping profiles.\n\n[https://sempoa.ai/projects/hm](https://sempoa.ai/projects/hm)\n\nwe wrote several blogs about it on our site, but feel free to have a play!\n"
    }
  ],
  "comments": [],
  "raw_markdown_by_id": {
    "2931742": "we have been very impressed by the many different approaches made by this community. hence we thought we implement our version as a web playground that anyone can test (with a view to be simplistic and practical).\n\nany user can browse the listings, and add (or remove) to cart any items they like. our recommendation engine works by monitoring the contents of the shopping cart, and recommend items based on \"nearest\" shopper that fits similar shopping profiles.\n\n[https://sempoa.ai/projects/hm](https://sempoa.ai/projects/hm)\n\nwe wrote several blogs about it on our site, but feel free to have a play!\n"
  }
}