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A Model-Driven Approach to Evolve Recommender Systems

Published: 16 October 2018 Publication History

Abstract

Recommender systems have become an important issue on Web applications, but its research is usually focused on algorithms and data optimization. However, as the recommendation techniques improve and these systems become more commonly used in software applications, there is the need of easily adapt and evolve them. To address this need, we propose a model-driven approach to evolve recommender systems and present an architecture solution from our research, using an events management system as the domain for an use-case scenario. Future work might demonstrate the architecture feasibility.

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WebMedia '18: Proceedings of the 24th Brazilian Symposium on Multimedia and the Web
October 2018
437 pages
ISBN:9781450358675
DOI:10.1145/3243082
© 2018 Association for Computing Machinery. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Published: 16 October 2018

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Author Tags

  1. model-driven engineering
  2. recommender systems
  3. software architecture

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WebMedia '18
WebMedia '18: Brazilian Symposium on Multimedia and the Web
October 16 - 19, 2018
BA, Salvador, Brazil

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WebMedia '18 Paper Acceptance Rate 37 of 111 submissions, 33%;
Overall Acceptance Rate 270 of 873 submissions, 31%

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