While recommender-system software libraries and APIs support you in developing a recommender system, a Recommender-System As-a-Service (RaaS) does all the work for you. Typically, you can integrate a recommender system into e.g. your e-commerce website or blog with a few clicks or lines of code. A RaaS comes with some compromises relating to flexibility, control and effectiveness when compared to a custom-made recommender system. However, a RaaS typically is highly scalable and delivers reasonable results after a few hours or even minutes — compared to months of development for a custom-made recommender system.
The following Google Sheet is work in progress. Please contact us if you would like to contribute to it.
The CORE recommender is recommender-system-as-a-service and API for research-paper recommendations (similar to my own service Mr. DLib). CORE has an impressive open source repository of over 25 millions full-text articles and the recommender system aims at digital libraries and other academic services. The CORE team recently did an interview with George Macgregor, Scholarly Publications & […]
Google joins the club of companies offering recommendations-as-a-service (RaaS). In a press release, Google announced the launch of “Product Discovery Solutions for Retail, Bolstering Personalized Online Shopping”. The ‘Product Discovery Solutions‘ consists of three modules, namely ‘Vision Product Search‘, Search for Retail (private Preview), and, most importantly for the readers of our Blog, ‘Recommendations AI‘, […]