Published 2020
| Version v4
Open dataset
Open
Advertisement CTR Prediction Data
Creators
Description
Description
Advertisement CTR (click-through-rate) prediction is the key problem in the area of computational advertising. Increasing the accuracy of advertisement CTR prediction is critical to improve the effectiveness of precision marketing. Based on the following datasets, a Kaggle competition was run for optimal advertisement CTR prediction models. The underlying datasets contain advertising behavior data collected from seven consecutive days, split up into a training dataset and a testing dataset. It is about 7GB large.
Files
test_data_A.csv__100lines.csv
Variables
| Name | Description |
|---|---|
| label | Label |
| uid | Unique user ID after data anonymization |
| task_id | Unique ID of an ad task |
| adv_id | Unique ID of an ad material |
| creat_type_cd | Unique ID of an ad creative type |
| adv_prim_id | Advertiser ID of an ad task |
| dev_id | Developer ID of an ad task |
| inter_typ_cd | Display form of an ad material |
| slot_id | Ad slot ID |
| spread_app_id | App ID of an ad task |
| tags | App tag of an ad task |
| app_first_class | App level-1 category of an ad task |
| app_second_class | App level-2 category of an ad task |
| age | User age |
| city | Resident city of a user |
| city_rank | Level of the resident city of a user |
| device_name | Phone model used by a user |
| device_size | Size of the phone used by a user |
| career | User occupation |
| gender | User gender |
| net_type | Network status when a behavior occurs |
| residence | Resident province of a user |
| his_app_size | App storage size |
| his_on_shelf_time | Release time |
| app_score | App rating score |
| emui_dev | EMUI version |
| list_time | Model release time |
| device_price | Device price |
| up_life_duration | HUAWEI ID lifecycle |
| up_membership_grade | Service membership level |
| membership_life_duration | Membership lifecycle |
| consume_purchase | Paid user tag |
| communication_onlinerate | Active time by mobile phone |
| communication_avgonline_30d | Daily active time by mobile phone |
| indu_name | Ad industry information |
| pt_d | Date when a behavior occurs |
Details
| Resource type | Open dataset |
| Title | Advertisement CTR Prediction Data |
| Creators |
|
| Research Fields | Business Administration Economics Psychology Sociology Political Science Economic & Social History Communication Sciences Educational Research Other |
| Size | 6.86 GB |
| Formats | Comma-separated values (CSV) (.csv) |
| License(s) | Undefined |
| External Resource | https://www.kaggle.com/louischen7/2020-digix-advertisement-ctr-prediction |