{
  "fetched_at": "2026-10-19T17:29:30Z",
  "source_url": "https://www.kaggle.com/competitions/2020-2/data",
  "pages": [
    {
      "name": "data-description",
      "content": "本页面是数据下载页面。一共包含5个数据文件。\n\ntrain.csv 是训练数据集，包含四列信息，分别是用户id、物品id、标签、时间戳。\n\ntest.csv 测试数据集，包含3列信息，分别是用户id、物品id和需要预测的标签。\n\nsample.csv 是提交结果文件，需要把test.csv中各行数据的预测结果整理成sample.csv的格式，sample.csv中各行与test.csv中的各行一一对应。\n\nmovies.tsv 是物品属性信息，包含3列信息，分别是物品id、名称、体裁(可能是多个，以|分割)\n\nuser.tsv 是用户属性信息表，包含5列信息，分别是用户id、性别、年龄、职业、地区编码。\n\n年龄信息对应关系如下：\n\n1: \"Under 18\"\n18: \"18-24\"\n25: \"25-34\"\n35: \"35-44\"\n45: \"45-49\"\n50: \"50-55\"\n56: \"56+\"\n职业信息代码对应关系：\n\n0: \"other\" or not specified\n1: \"academic/educator\"\n2: \"artist\"\n3: \"clerical/admin\"\n4: \"college/grad student\"\n5: \"customer service\"\n6: \"doctor/health care\"\n7: \"executive/managerial\"\n8: \"farmer\"\n9: \"homemaker\"\n10: \"K-12 student\"\n11: \"lawyer\"\n12: \"programmer\"\n13: \"retired\"\n14: \"sales/marketing\"\n15: \"scientist\"\n16: \"self-employed\"\n17: \"technician/engineer\"\n18: \"tradesman/craftsman\"\n19: \"unemployed\"\n20: \"writer\"",
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    },
    {
      "name": "Description",
      "content": "这里是2020级《智能推荐》第二部分知识竞赛，请采用第二部分所学知识进行比赛。\n第二部分知识包括：SVD、LFM、带偏置的LFM、SVD++、逻辑回归、FM、FFM、GBDT+LR、LS-PLM、embedding等算法。\n\n注意：以上内容可以任意组合使用，但是不能使用超出以上内容的算法。\n\n本次竞赛是点击率预估问题，请将测试集中所有的数据预估0/1标签，代表不点击/点击。\n\n采用计算准确率的方式来评估。正例预测正确的个数+负例预测正确的个数 / 总样本数\n\ncsv格式的文件，文件中有2列，第1列为ID；第2列为预测标签。\n\nid,rating\n1,0\n2,0\n3,1\netc…",
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    },
    {
      "name": "Evaluation",
      "content": "本次竞赛是点击率预估问题，请将测试集中所有的数据预估0/1标签，代表不点击/点击。\n\n采用计算准确率的方式来评估。正例预测正确的个数+负例预测正确的个数 / 总样本数",
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    },
    {
      "name": "rules",
      "content": " - Don't cheat!\n - Apply yourself!\n - Have fun!",
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}