Our released dataset ORAD-Pub could be found at JD JingPan with password 3jhbd6.
In the data files, each row corresponds to a search session.
Each column is a piece of multiple sample data aggregated according to user-query. The organization form of each column is: column[0]: user_id. int type column[1]: query_id. int type column[2]: The source of each sample(0:advertising. 1:organic). list type column[3]: The label of each sample. list type column[4:]: the side info [itemID, categoryID, brandID, vendorID and priceID] of each sample. list type
Requirements
python 3.6.13
tensorflow 1.15.0
scikit-learn 0.24.2
Quick start
Create a new data folder and put the downloaded dataset into the folder. Then,
Implicit User Awareness Modeling via Candidate Items for CTR Prediction in Search Ads
This repo is the official implementation for the SIGIR 2023 paper: LOVF: Layered Organic View Fusion for Click-through Rate Prediction in Online Advertising.
Data format
Our released dataset ORAD-Pub could be found at JD JingPan with password
3jhbd6.In the data files, each row corresponds to a search session. Each column is a piece of multiple sample data aggregated according to user-query. The organization form of each column is:
column[0]: user_id. int type
column[1]: query_id. int type
column[2]: The source of each sample(0:advertising. 1:organic). list type
column[3]: The label of each sample. list type
column[4:]: the side info [itemID, categoryID, brandID, vendorID and priceID] of each sample. list type
Requirements
Quick start
Create a new
datafolder and put the downloaded dataset into the folder. Then,