# 技巧

在推荐数据越来越大的今天，一方面需要有好的硬件支撑，一方面是好的工具实现。2023年初这段时间，[polars](https://www.pola.rs/)在赛圈越来越火就是一个例子。

模型方向

* 树： count feature(是否使用test的leak信息), embedding feature, target encoding
* NN: 交叉特征，序列信息

## 召回

* itemCF经典操作参考：江离cikm 2019
* 规则：同类别，最HOT，近期兴趣
* word2vec
* FAISS
* YouTube-DNN

## 排序

## 优化

* 冷启动问题
* 行为序列建模
* 图关系

## 特征

* 降维查看user item embedding的区分度

## 参考与阅读

**Overall**

* 召回：https://zhuanlan.zhihu.com/p/353436475
* 排序：https://zhuanlan.zhihu.com/p/550513066
* https://github.com/wzhe06/SparrowRecSys
* https://github.com/microsoft/recommenders
* https://github.com/mJackie/RecSys
* https://zhuanlan.zhihu.com/p/351190043
* https://github.com/xingzhexiaozhu/MovieRecommendation
* https://github.com/ZiyaoGeng/Recommender-System-with-TF2.0
* CTR: https://zhuanlan.zhihu.com/p/104307718
* https://zhuanlan.zhihu.com/p/109933924
* https://github.com/DeepGraphLearning/RecommenderSystems
* https://github.com/zhaozhiyong19890102/Recommender-System
* https://github.com/jihoo-kim/awesome-RecSys
* https://github.com/datawhalechina/fun-rec
* KDD https://github.com/aister2020?tab=repositories
* https://github.com/DeepGraphLearning/RecommenderSystems
* https://github.com/wangshusen/RecommenderSystem
* https://github.com/ChuanyuXue/Recommender-Systems-Competition-TopSolutions
* https://zhuanlan.zhihu.com/p/351190043
* https://github.com/oreilly-japan/RecommenderSystems

FM: 解决数据稀疏的情况下，特征怎样组合的问题

* https://www.cnblogs.com/Allen-rg/p/10750393.html
* http://d2l.ai/chapter\_recommender-systems/fm.html
* https://www.zhihu.com/question/362190044/answer/1670206355
* 工程化trick：https://zhuanlan.zhihu.com/p/341452558
* https://github.com/jfpuget/LibFM\_in\_Keras/blob/master/keras\_blog.ipynb
* https://zhuanlan.zhihu.com/p/58160982
* https://zhuanlan.zhihu.com/p/145436595
*

FFM：

* https://zhuanlan.zhihu.com/p/347014236
* https://zhuanlan.zhihu.com/p/328481154
* https://github.com/nzc/tencent-contest

SINE:

* https://github.com/lambdaji/tf\_repos
* 微信看一看： http://blog.itpub.net/31559354/viewspace-2704029/
* https://www.zhihu.com/question/451498156/answer/1802577845

粗排：

* https://zhuanlan.zhihu.com/p/355828527

入门：

* https://tianchi.aliyun.com/competition/entrance/531842/forum
* https://zhuanlan.zhihu.com/p/353436475
* https://bjt.name/2018/07/03/bpr.html
* https://github.com/ikaruga0508/tianchi\_news\_pub
* https://github.com/LogicJake/tuling-video-click-top3
* https://github.com/miziha-zp/BiuG-XMRec-WSDMCup22

https://github.com/opdai/wsdm2022-xmrec-top1-solution

https://github.com/gaolinjie/awesome-recommender-systems

https://github.com/tensorflow/ranking\
https://github.com/hongleizhang/RSPapers

https://github.com/rn5l/rsc19

https://zhuanlan.zhihu.com/p/139256086

* https://zhuanlan.zhihu.com/p/353436475
* https://zhuanlan.zhihu.com/p/35046241
* https://github.com/ChuanyuXue/Recommender-Systems-Competition-TopSolutions
* https://github.com/CharlesPikachu/algorithm/tree/master/python/SortingAlgorithm
* https://neptune.ai/blog/tabular-data-binary-classification-tips-and-tricks-from-5-kaggle-competitions
* https://github.com/alibaba/EasyRec/tree/master/easy\_rec/python/model
