数据挖掘学习-准备篇-数据集
1.Recsys2013 Yelp
https://www.kaggle.com/c/yelp-recsys-2013/data
https://www.yelp.com/dataset_challenge/dataset
训练数据集=yelp_training_set.zip
此数据集的博客
2.各种kaggle数据集
https://www.kaggle.com/datasets
3.Santander银行产品推荐方案
https://www.kaggle.com/c/santander-product-recommendation/data
4.各种数据集
17 must-have data science projects to enhance your expertise and practical skills. These projects are not only challenging but also rewarding, allowing you to apply theoretical knowledge in real-world scenarios. By engaging with these 17 must-have data science projects, you can solidify your understanding of key concepts, develop hands-on experience, and stay updated with the latest trends in the field. Each project is carefully curated to provide a comprehensive learning experience that will help you build a strong foundation in data science. Whether you're a beginner or an intermediate learner, these 17 must-have data science projects will guide you toward achieving your goals in this dynamic and growing field.
5.雅虎音乐数据集
yahoo music dataset，kdd_cup_dataset
6.Flixster Dataset: 观众在弗利克斯特数据库中对电影实施的评分行为与其社交关系数据。 http://www.sfu.ca/~sja25/datasets/
7.
另外还有一些社交网络分析的数据集
http://snap.stanford.edu/na09/resources.html
http://snap.stanford.edu/data/
主页
- GroupLens项目官方主页：http://www.grouplens.org
- Grouplens的领导者：John Riedl http://www-users.cs.umn.edu/~riedl/
- 推荐系统领域最有影响力的博客维护者：Greg Linden
- ResysChina发起人：谷文栋 http://www.guwendong.com
- XLVector博士：Xlvector http://xlvector.net
第三方开源推荐
1.MyMediaLite 是一个轻量级的多用途的推荐系统的算法库。
http://mymedialite.net/download/index.html
2.EasyRec http://www.easyrec.org/
会议
自2009年以来由ACM主办的年度学术会议包括但不限于RecSys（Recommender Systems Conference）、CARS（Context-Aware Recommender Systems Workshop）、ACM EC、KDD、SIGIR、UMAP、IUI、CHI、CIKM、ECAI、ECIR等；此外还包括IEEE TKDE（IEEE Transactions on Knowledge and Data Engineering）、IEEE Intelligent System等期刊以及ACM TKDD（ACM Transactions on Knowledge Discovery from Data）等专业期刊。