InBeat: JavaScript recommender system supporting sensor input and linked data

doi:10.1016/j.knosys.2017.07.026

InBeat: JavaScript recommender system supporting sensor input and linked data

2017-11-01

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DOI：10.1016/j.knosys.2017.07.026

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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. (C) 2017 The Authors. Published by Elsevier B.V.

Keyword:

Recommender system

Semantic web

Association rules

Sensors

InBeat: JavaScript recommender system supporting sensor input and linked data

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