aliang-rec Goto Github PK

agnn

Zero-shot Video Object Segmentation via Attentive Graph Neural Networks (ICCV2019 Oral)

aitm

TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework. Code for the paper accepted by KDD21: Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising. [https://arxiv.org/abs/2105.08489]

algorithm-practice-in-industry

搜索、推荐、广告、用增等工业界实践文章收集（来源：知乎、Datafuntalk、技术公众号）

amazon-din-tfrecord-estimator

anchorkg

atrank

这是阿里巴巴和北大联合发表的一篇论文，在电商环境中，用户会存在多种行为：浏览、购买、收藏商品，领取、使用优惠券，搜索关键词等等

benchmark

causalmta

causerec

chameleon_recsys

Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems

chaml

Curriculum Meta-Learning for Next POI Recommendation

clrec

Pytorch implementation for "Does Continual Learning = Catastrophic Forgetting?"

code-for-mamo

The code for paper MAMO: Memory-Augmented Meta-Optimization for Cold-start Recommendation

cogdl

CogDL: An Extensive Toolkit for Deep Learning on Graphs (Graph Neural Networks, GNN)

crosscbr

dawar

dbrl

Dataset Batch(offline) Reinforcement Learning for recommender system

decrs

Deconfounded Recommendation for Alleviating Bias Amplification

deep-ctr-prediction

CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)

deep-listwise-context-model-for-ranking-refinement

A Tensorflow implementation of the Deep Listwise Context Model (DLCM) for ranking refinement.

deep-reinforcement-learning-for-list-wise-recommendations

Markov Decision Process and Deep-Q-Network

deepctr

Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

deeprec

DeepRec is a recommendation engine based on TensorFlow.

dl-mia-kdd-2022

drl-rec

Deep reinforcement learning for recommendation system

dynamic-fairness

Dynamic Fair Rankings

easyrec

A framework for large scale recommendation algorithms.

estimator

train, evaluate and deploy model using tf-estimator

federatedscope

An easy-to-use federated learning platform

flink-recommandsystem-demo

:helicopter::rocket:基于Flink实现的商品实时推荐系统。flink统计商品热度，放入redis缓存，分析日志信息，将画像标签和实时记录放入Hbase。在用户发起推荐请求后，根据用户画像重排序热度榜，并结合协同过滤和标签两个推荐模块为新生成的榜单的每一个产品添加关联产品，最后返回新的用户列表。