shenweichen/DSIN
Code for the IJCAI'19 paper "Deep Session Interest Network for Click-Through Rate Prediction"
This project helps e-commerce companies and online advertisers improve their ad recommendation systems. By taking historical user click data and ad display information, it predicts which ads users are most likely to click on. This allows advertising platforms and marketing teams to deliver more relevant ads, increasing engagement and conversion rates.
447 stars. No commits in the last 6 months.
Use this if you are an e-commerce platform, advertiser, or data scientist in online advertising looking to build or evaluate advanced models for predicting ad click-through rates based on user session behavior.
Not ideal if you are looking for a complete, production-ready ad serving or recommendation system, or if your primary goal is not focused on click-through rate prediction for display advertising.
Stars
447
Forks
132
Language
Python
License
Apache-2.0
Category
Last pushed
May 23, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/shenweichen/DSIN"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
NVIDIA-Merlin/HugeCTR
HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training
shenweichen/DeepCTR-Torch
【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.
shenweichen/DeepCTR
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
UlionTse/mlgb
MLGB is a library that includes many models of CTR Prediction & Recommender System by TensorFlow...
cnkuangshi/LightCTR
Lightweight and Scalable framework that combines mainstream algorithms of Click-Through-Rate...