【The Task】

Given a sequence of click events performed by some user during a typical session in an e-commerce website, the goal is to predict whether the user is going to buy something or not, and if he is buying, what would be the items he is going to buy. The task could therefore be divided into two sub goals:

  1. Is the user going to buy items in this session? Yes|No
  2. If yes, what are the items that are going to be bought?

【The Data】

Training Data Files

The training data comprises two different files:

  1. yoochoose-clicks.dat - Click events. Each record/line in the file has the following fields:
    1. Session ID – the id of the session. In one session there are one or many clicks.
    2. Timestamp – the time when the click occurred.
    3. Item ID – the unique identifier of the item.
    4. Category – the category of the item.
  2. yoochoose-buys.dat - Buy events. Each record/line in the file has the following fields:
    1. Session ID - the id of the session. In one session there are one or many buying events.
    2. Timestamp - the time when the buy occurred.
    3. Item ID – the unique identifier of item.
    4. Price – the price of the item.
    5. Quantity – how many of this item were bought.

The Session ID in yoochoose-buys.dat will always exist in the yoochoose-clicks.dat file – the records with the same Session ID together form the sequence of click events of a certain user during the session. The session could be short (few minutes) or very long (few hours), it could have one click or hundreds of clicks. All depends on the activity of the user.

Test File

The Test data is one file:

  1. yoochoose-test.dat - identically structured as the yoochoose-clicks.dat of the training data
    1. Session ID
    2. Timestamp
    3. Item ID
    4. Category

via:  http://2015.recsyschallenge.com/challenge.html

RecSys Challenge 2015的更多相关文章

  1. 大规模视觉识别挑战赛ILSVRC2015各团队结果和方法 Large Scale Visual Recognition Challenge 2015

    Large Scale Visual Recognition Challenge 2015 (ILSVRC2015) Legend: Yellow background = winner in thi ...

  2. Codechef May Challenge 2015

    随便瞎写,其实没做出多少题: Chef and Cake 题目大概是用输入的数生成 一个数组并且生成出q个[X,Y]的询问, 数组长度N<=1000000,q<=10^7; 开始用线段树, ...

  3. Kaggle : Display Advertising Challenge( ctr 预估 )

    原文:http://blog.csdn.net/hero_fantao/article/details/42747281 Display Advertising Challenge --------- ...

  4. (转) Awesome - Most Cited Deep Learning Papers

    转自:https://github.com/terryum/awesome-deep-learning-papers Awesome - Most Cited Deep Learning Papers ...

  5. RNN and LSTM saliency Predection Scene Label

    http://handong1587.github.io/deep_learning/2015/10/09/rnn-and-lstm.html  //RNN and LSTM http://hando ...

  6. [转]NLP Tasks

    Natural Language Processing Tasks and Selected References I've been working on several natural langu ...

  7. Recsys2018 music recomendation

    http://www.recsyschallenge.com/2018/ January 2018 Release of the "One Million Playlists" d ...

  8. 「LOJ#10051」「一本通 2.3 例 3」Nikitosh 和异或(Trie

    题目描述 原题来自:CODECHEF September Challenge 2015 REBXOR 1​​≤r​1​​<l​2​​≤r​2​​≤N,x⨁yx\bigoplus yx⨁y 表示 ...

  9. Paper | U-Net: Convolutional Networks for Biomedical Image Segmentation

    目录 故事背景 U-Net 具体结构 损失 数据扩充 发表在2015 MICCAI.原本是一篇医学图像分割的论文,但由于U-Net杰出的网络设计,得到了8k+的引用. 摘要 There is larg ...

随机推荐

  1. BZOJ 3544 [ONTAK2010]Creative Accounting(set)

    [题目链接] http://www.lydsy.com/JudgeOnline/problem.php?id=3544 [题目大意] 找一段区间使得Σai mod m的值最大. [题解] 首先计算前缀 ...

  2. [xsy3241]暴风士兵

    题意:一个血量为$h$的人,它会被攻击$n$次,第$i$次有$p$的概率$-1$滴血(每次的$p$不同),问每次攻击后他的血量期望,强制在线 若一个人被扣了$i$滴血的概率为$p_i$,那么记多项式$ ...

  3. bootstrapTable定位行固定滚动条

    写在前面: 当页面table列表数据有修改后,用户需要再次回到修改的行位置. 1.当修改行数据后,table刷新,行数据位置前后不发生改变 ,可使用下面这种方法: /*获取当前滚动条的位置*/ var ...

  4. CDOJ 1281 暴兵的卿学姐 构造题

    暴兵的卿学姐 题目连接: http://acm.uestc.edu.cn/#/problem/show/1281 Description 沈宝宝又和卿学姐开始玩SC2了! 自从沈宝宝学会新的阵型后,就 ...

  5. MongoDB 刷新几次就报错

    官方: MongoDB.Driver 在页面上 速度刷新几次,就会抛错? 为何? Service 层  Autofac

  6. arcgis andriod 点击后变色

    <RelativeLayout xmlns:android="http://schemas.android.com/apk/res/android" xmlns:tools= ...

  7. C++ Java C#泛型

    泛型概述C#中的泛型C#泛型和java泛型的比较C#泛型和C++模板的比较C#泛型中的约束 泛型概述 Bruce Eckel :您能对泛型做一个快速的介绍么? Anders Hejlsberg : 泛 ...

  8. Windows Server 2008 远程桌面连接拒绝

    (1)远程连接的时候在本地用户名添加域名 现象:在Windows2008R2配置成域控制器前,还没有安装AD,管理员Admistrator以及新创建的用户(创建的时候将该用户加入远程桌面管理组),发现 ...

  9. ylbtech-LanguageSamples-Versioning(版本控制)

    ylbtech-Microsoft-CSharpSamples:ylbtech-LanguageSamples-Versioning(版本控制) 1.A,示例(Sample) 返回顶部 “版本控制”示 ...

  10. 创建CrawlSpider爬虫简要步骤

    创建CrawlSpider爬虫简要步骤: 1. 创建项目文件: e.g: scrapy startproject douyu (douyu为项目名自定义) 2. 进入项目文件: e.g: cd dou ...