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RECOLIBRY-CORE: A component-based framework for building recommender systems

delete2019-10-01
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AI
J
José L. Jorro-Aragoneses *
J
Juan A. Recio-Garcí­a
B
Belén Díaz‐Agudo
G
Guillermo Jiménez-Díaz
DOI:10.1016/j.knosys.2019.07.025delete
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Abstract

Abstract

En 中文
Recommendation systems are a key part of almost every modern consumer website. These systems include techniques to filter, explore and rank a huge amount of information based on users' preferences or similar items. Designing and implementing a recommender system from scratch require skills of programming and recommending technologies. In this paper we describe RECOLIBRY-CORE, a framework to develop recommender systems based on the reuse of components provided by third-party frameworks. (C) 2019 Elsevier B.V. All rights reserved.
Keywords:
Recommender systems
Component-based development
Java
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

K
Knowledge-Based Systems
IF:
7.6
Papers:
1.2W
Citations:
4.5W

Organization

C
Complutense University of Madrid
Scholars:
2.6W
Papers: 2.2W
Citations: 31