# Tencent2019_Preliminary_Rank1st

**Repository Path**: wwfcoder/Tencent2019_Preliminary_Rank1st

## Basic Information

- **Project Name**: Tencent2019_Preliminary_Rank1st
- **Description**: 腾讯广告算法大赛-The code for 2019 Tencent College Algorithm Contest, and the online result ranks 1st in the preliminary.
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2019-07-16
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

### 1. 题目介绍

请直接查看guide.pdf了解赛题，该项目是初赛第一名的模型。

### 2.模型介绍

![avatar](picture/framework.png)

![avatar](picture/CIN.png)

![avatar](picture/key-value.png)

### 3. 配置环境

- scikit-learn
- tqdm
- pandas
- numpy
- scipy
- tensorFlow=1.12.0 (其他版本≥1.4且不等于1.5或1.6)
- Linux Ubuntu 16.04, 128G内存(64G应该足够)，一张显卡 

### 4.数据下载

从该 [网页](https://amritasaha1812.github.io/CSQA/download/)下载数据，并解压到data目录，或:

```shell
mkdir data 
cd data
wget https://www.dropbox.com/s/x2scxmk8q0p0xae/algo.qq.com_641013010_testa.zip
unzip algo.qq.com_641013010_testa.zip imps_log.zip user.zip
cd ..
```

**注：需要VPN访问国外的网络**

### 5.数据预处理

```shell
python src/preprocess.py
```

### 6.提取特征

```shell
python src/extract_feature.py
```

### 7.转换数据格式

```shell
python src/convert_format.py
```

1）缺失值NA用0填充

2）将Word2Vec和DeepWalk得到的embedding拼接起来，并且掩盖到5%的广告

3）将需要用key-values的稠密特征正则化到[0,1]之间

### 8.训练模型

```shell
mkdir submission
python train.py
```