InBeat: JavaScript recommender system supporting sensor input and linked data

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摘要

Interest Beat (inbeat.eu) is an open source recommender framework that fulfills some of the demands raised by emerging applications that infer ratings from sensor input or use linked open data cloud for feature expansion. As a recommender algorithm, InBeat uses association rules, which allow to explain why a specific recommendation was made. Due to modular architecture, other algorithms can be easily plugged in. InBeat has a pure JavaScript version, which allows to confine processing to a client-side device. There is a performance optimized server-side bundle, which succesfully participated in two recent recommender competitions involving large volumes of streaming data. InBeat works on a number of platforms and is also available for Docker.

论文关键词:Recommender system,Semantic web,Association rules,Sensors

论文评审过程:Received 8 December 2016, Revised 18 July 2017, Accepted 19 July 2017, Available online 20 July 2017, Version of Record 22 September 2017.

论文官网地址:https://doi.org/10.1016/j.knosys.2017.07.026