A look inside TikTok’s all-knowing algorithm [Charlotte Hu]
The New York Times recently reported about leaked documents on how Tik Tok’s recommender system works (PayWall). The report followed an investigation of the Wall Street Journal on the same topic (also PayWall). Charlotte Hu from “Popular Science” summarized the reports.
More: https://www.popsci.com/technology/tiktok-algorithm/.
Facebook documents its recommender system — a little bit. [Sarah Perez @ Techcrunch]
How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages? [Dokyun Lee & Kartik Hosanagar]
Case study how simple recommendation techniques improve user experience in e-Commerce [Emilio Carrión @ MercadonaTech]
About The Author
Joeran Beel
I am the founder of Recommender-Systems.com and head of the Intelligent Systems Group (ISG) at the University of Siegen, Germany https://isg.beel.org. We conduct research in recommender-systems (RecSys), personalization and information retrieval (IR) as well as on automated machine learning (AutoML), meta-learning and algorithm selection. Domains we are particularly interested in include smart places, eHealth, manufacturing (industry 4.0), mobility, visual computing, and digital libraries. We founded or maintain, among others, LensKit-Auto, Darwin & Goliath, Mr. DLib, and Docear, each with thousand of users; we contributed to TensorFlow, JabRef and others; and we developed the first prototypes of automated recommender systems (AutoSurprise and Auto-CaseRec) and Federated Meta Learning (FMLearn Server and Client).