Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4946049 | Knowledge-Based Systems | 2017 | 4 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Jaroslav KuchaÅ, TomáÅ¡ Kliegr,