4 Matching Annotations
  1. Dec 2022
  2. Dec 2018
    1. https://www.jiqizhixin.com/technologies/6ca1ea2d-6bca-45b7-9c93-725d288739c3

      https://time.geekbang.org/column/intro/74?utm_source=website&utm_medium=infoq&utm_campaign=recommend&utm_content=wudao01start

      https://blog.csdn.net/zhufenglonglove/article/details/51602162

      关于推荐的多种形式,看一看 coursera 这一节课: Movielens Tour

      https://www.coursera.org/learn/recommender-systems-introduction/lecture/HcINn/movielens-tour

      movielens 网址: https://movielens.org/

      很经典

      1. 如何用 Lambda 架构做实时推荐

      https://www.researchgate.net/profile/Thanisa_Numnonda/publication/322130766_A_real-time_recommendation_engine_using_lambda_architecture/links/5b175be30f7e9b1912b3971a/A-real-time-recommendation-engine-using-lambda-architecture.pdf?origin=publication_detail

      1. 从头开始做推荐系统

      https://aironman2k.wordpress.com/2016/06/09/about-how-to-build-a-recommendation-engine-using-kafka-spark-streaming-using-scala/

      1. 上面的文章作者写的工程代码 github

      https://github.com/alonsoir/awesome-recommendation-engine

      1. github 上的推荐系统 from scratch

      https://github.com/alonsoir/recomendation-spark-engine

      1. 网络论文 关于 spark 构建实时推荐

      http://ceur-ws.org/Vol-1609/16090628.pdf

      1. Streaming data analytics design patterns

      https://www.slideshare.net/Hadoop_Summit/design-patterns-for-real-time-streaming-data-analytics-49480337

      1. 超经典实时推荐系统 PPT

      https://www.slideshare.net/HadoopSummit/real-time-streaming-advanced-analytics-approximations-and-recommendations-using-apache-spark-mlgraph-x-kafka-stanford-corenlp-and-twitter

      DONE: 5. 国内博客非常好: spark-streaming 实时推荐系统

      https://blog.csdn.net/pztyz314151/article/details/53025728