Extending RapidMiner with recommender systems algorithms
Matej Mihelčić, Nino Antulov-Fantulin, Matko Bošnjak, Tomislav Šmuc · 2012
Recommender systems are ubiquitous in today’s information overloaded world. They help users to find and select products from a huge number available in various sources. RapidMiner can be used to construct various information filtering workflows using various data mining techniques. However, it does not explicitly support typical recommendation tasks. In this paper we present a RapidMiner Recommender Extension, developed in order to embed some of the state-of-the-art recommendation techniques into RapidMiner. We present the functionality of the extension, along with examples of diverse recommender system implementations. Integration of the extension with RapidAnalytics, which allows seamless construction of production level recommender systems, is demonstrated.