🛠 Contribute: Found a typo? Or any other change in the description that you would like to see? Please consider sending us a pull request in the public repo of the challenge here.
🕵️ Introduction
Open up the black box of online advertising with this problem! What makes people click on ads? 🤔 This is a question that digital marketers have been asking themselves for years! An ad can fail or succeed for reasons that might have nothing to do with its content or relatability. But can we bring some predictability to it with the help of AI?
Given some crucial information on an online ad
, can you predict
whether it will be clicked
or not?
Understand with code! Here is getting started code
for you.😄
💾 Dataset
The dataset provided contains advertisements that were shown along side search results and whether or not they were clicked on. For each advertisement, 11 properties are given:
Click
- 1 if the add was clicked, 0 if it was not clickedimpression
- number of sessions in which the Ad was shown to the userID who issued the queryurl_hash
- a hash of the url on which the ad was displayedAdID
- an id uniquely identifying an adadvertiserID
- an id uniquely identifying an advertiserDepth
- number of ads displayed to a user in a sessionPosition
- order of an ad in a displayquery_id
- an id uniquely identifying a querykeyword_id
- an id uniquely identifying a search keywordtitle_id
- an id uniquely identifying the title of the addescription_id
- an id uniquely identifying a description of the aduser_id
- an id uniquely identifying a user
📁 Files
Following files are available in the resources
section:
-
train.csv
- (40000
samples) This csv file contains the attributes describing an advertisement along with the binary value denoting whether or not the advertisement was clicked on. -
test.csv
- (10000
samples) File that will be used for actual evaluation for the leaderboard score but does not have the binary value denoting whether or not the advertisement was clicked on.
🚀 Submission
- Prepare a CSV containing header as
click
and predicted value as digit0
or1
respectively denoting whether or not the corresponding ad will be clicked upon. - Name of the above file should be
submission.csv
. - Sample submission format available at
sample_submission.csv
in the resorces section.
Make your first submission here 🚀 !!
🖊 Evaluation Criteria
During evaluation F1 score will be used to test the efficiency of the model where,
🔗 Links
- 💪 Challenge Page: https://www.aicrowd.com/challenges/adclk
- 🗣️ Discussion Forum: https://www.aicrowd.com/challenges/adclk/discussion
- 🏆 Leaderboard: https://www.aicrowd.com/challenges/adclk/leaderboards