{
  "fetched_at": "2026-10-24T16:48:21Z",
  "source_url": "https://www.kaggle.com/competitions/ee627-19s/data",
  "pages": [
    {
      "name": "rules",
      "content": "\n\t<!-- Begin Base Rules -->\n    <h3>One account per participant</h3>\n    <p>You cannot sign up to Kaggle from multiple accounts and therefore you cannot submit from multiple accounts.</p>\n    <h3>No private sharing outside teams</h3>\n    <p>\n        Privately sharing code or data outside of teams is not permitted.\n        It's okay to share code if made available to all participants on the forums.\n    </p>\n\n    <h3>Team Limits</h3>\n    <p>The maximum team size is 3.</p>\n    <h3>Submission Limits</h3>\n    <p>You may submit a maximum of 3 entries per day.</p>\n    <p>You may select up to 2 final submissions for judging.</p>\n    <h3>Competition Timeline</h3>\n    <p>Start Date: <strong>10/30/2018  12:00 AM UTC</strong></p>\n    <p>Merge Deadline: <strong>12/18/2018  12:00 AM UTC</strong></p>\n    <p>Entry Deadline: <strong>12/18/2018 12:00 AM UTC</strong></p>\n    <p>End Date: <strong>12/25/2018 12:00 AM UTC</strong></p>\n\t<!-- End Base Rules -->",
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    {
      "name": "data-description",
      "content": "<h3>Overview</h3>\n<ul>\n<li><strong>trainIterm2.txt</strong> - the training set</li>\n<li><strong>testIterm2.txt</strong> - the test set</li>\n\n<li><strong> sample_\nsubmission.csv </strong> - a sample submission file in the correct format</li>\n\n- **trackData2.txt** -- Track information formatted as: <'TrackId'>|<'AlbumId'>|<'ArtistId'>|<'Optional GenreId_1'>|...|<'Optional GenreId_k'>\n- **albumData2.txt** -- Album information formatted as: <'AlbumId'>|<'ArtistId'>|<'Optional GenreId_1'>|...|<'Optional GenreId_k'>\n- **artistData2.txt** -- Artist listing formatted as: <'ArtistId'>\n- **genreData2.txt** -- Genre listing formatted as: <'GenreId'>\n",
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    {
      "name": "Description",
      "content": "This is the final challenge of the EE627 course.\n\nNowadays, technology companies often use recommender algorithm to recommend products,  music, movie, etc. Recommender algorithm is really useful and helps all those companies make a huge profit. \n\nNow, after learning the factorial matrix and other useful algorithms. It's your turn to solve the problem which Spotify, Amazon, and Yahoo Music faced every day - recommend music to their customers.",
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    {
      "name": "Evaluation",
      "content": "Submissions are evaluated on area under the ROC curve between the predicted probability and the observed target.\n\n###Submission\nFor each TrackID in the test set, you must predict wheter we should recommmed this track. The file should contain a header and have the following format:\n<pre>TrackID, Predictor<br>1          1<br></pre>",
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    {
      "name": "Prize And Bonus",
      "content": "We will give the top three teams  bonus points and for those who can surpass last years records 0.8715 they will also earned an extra points. ",
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