{
  "fetched_at": "2026-10-19T08:06:14Z",
  "source_url": "https://www.kaggle.com/competitions/airbnb-new-user/data",
  "pages": [
    {
      "name": "data-description",
      "content": "In this challenge, you are given a list of users along with their demographics, web session records, and some summary statistics. You are asked to predict which country a new user's first booking destination will be. All the users in this dataset are from the USA.\n\nThere are 12 possible outcomes of the destination country: 'US', 'FR', 'CA', 'GB', 'ES', 'IT', 'PT', 'NL','DE', 'AU', 'NDF' (no destination found), and 'other'. Please note that 'NDF' is different from 'other' because 'other' means there was a booking, but is to a country not included in the list, while 'NDF' means there wasn't a booking.\n\nThe train and test splits are random. The data in the train set dates back to 2010, while the test set consists of users joining after 01/04/2014. The sessions data dates back to 2014. \n\n#File Descriptions\ntrain.csv - the training set  \ntest.csv - the test set  \nsample_submission.csv - an example of the submission file in the correct format  \n\nFor information on data fields, please visit: https://www.kaggle.com/c/airbnb-recruiting-new-user-bookings/data",
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      "name": "Description",
      "content": "<p>New users on Airbnb can book a place to stay in 34,000+ cities across 190+ countries. Predicting the region of booking will help provide better content to the users with regard to their choice of destination, decrease the average time to first booking, and better forecast demand, thus benefitting both the customers and Airbnb.</p>\n\n<p>We challenge the IIITB students to predict the country where a new user will choose to make their first booking.</p>\n",
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      "name": "Evaluation",
      "content": "The evaluation metric for this competition is NDCG (Normalized discounted cumulative gain) @ k where k=3.\n\n#Submission File\nFor each new user, you are to make a maximum of 3 predictions on the country of the first booking. The file should contain a header and have the following format:\n\n    id,country_destination\n    f3g7ae12j0,NDF\n    ks0uq0sd8x,NDF\n    8w236a1unv,NDF\n    vd221xgcu6,NDF\n    etc.\n\nEach prediction should be in a new row. However, all the predictions for a user must be made one after the other and ordered such that the most probable destination country goes first.",
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    {
      "name": "rules",
      "content": "<h2>One account per participant</h2>\n<p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\n<h2>No private sharing outside teams</h2>\n<p>Privately sharing code or data outside of teams is not permitted. It's okay to share code if made available to all participants on the forums. </p>\n<h2>Team Mergers</h2>\n<p>Team mergers are allowed in this competition and deadline for team mergers is 23rd Sept, 2020 11:59 PM IST.</p>\n<h2>Team Limit</h2>\n<p>Maximum Team Size is 3.</p>\n<h2>General Guidelines</h2>\n<ul>\n<li>Use of any pretrained model is not allowed.</li>\n<li>Any use of deep learning approaches is not allowed. Please stick to classical approaches.</li>\n<li>No use of External Data is allowed, only the data provided with the competition has to be used.</li>\n</ul>\n<h2>Submission Limit</h2>\n<p>You may submit a maximum of 5 entries per day till 10th Oct, 2020 11:59 PM IST and 2 submissions after that.<br>\nYou may select up to 2 final submissions for judging.</p>\n<h2>Competition Deadline</h2>\n<p>End Date: 18th Dec, 2020 11:59 PM IST</p>",
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