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In the past decades recommender systems have become a powerful tool to improve personalization on the Web. Yet, many popular websites lack such functionality, its implementation usually requires certain technical skills, and, above all, its introduction is beyond the scope and control of end-users. To alleviate these problems, this paper presents a novel tool to empower end-users without programming skills, without any involvement of website providers, to embed personalized recommendations ofdoi:10.1007/s11042-020-09803-8 fatcat:iryiw3kjrbfqhoizwih2zxmwkm