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In this work, we tackle the problem of adapting a real-time recommendersystem to multiple application domains, and their underlying data models andcustomization requirements. To do that, we present Uptrendz, a multi-domainrecommendation platform that can be customized to provide real-timerecommendations in an API-centric way. We demonstrate (i) how to set up areal-time movie recommender using the popular MovieLens-100k dataset, and (ii)how to simultaneously support multiple application domains based on theuse-case of recommendations in entrepreneurial start-up founding. For that, wedifferentiate between domains on the item- and system-level. We believe thatour demonstration shows a convenient way to adapt, deploy and evaluate arecommender system in an API-centric way. The source-code and documentationthat demonstrates how to utilize the configured Uptrendz API is available onGitHub.

Uptrendz: API-Centric Real-time Recommendations in Multi-Domain Settings