e-Commerce product classification: our participation at cDiscount 2015 challenge
This work addresses product classification for e-commerce applications, but it is incremental as it uses existing linear models and voting systems.
The authors tackled product classification in e-commerce by participating in the cDiscount 2015 challenge, achieving an accuracy of 64.20% and ranking 10th out of 175 teams.
This report describes our participation in the cDiscount 2015 challenge where the goal was to classify product items in a predefined taxonomy of products. Our best submission yielded an accuracy score of 64.20\% in the private part of the leaderboard and we were ranked 10th out of 175 participating teams. We followed a text classification approach employing mainly linear models. The final solution was a weighted voting system which combined a variety of trained models.