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

José L. Jorro-Aragoneses

doi:10.1016/j.knosys.2019.07.025

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

2019-10-01

6

PRE

AI

J

José L. Jorro-Aragoneses *

Guillermo Jiménez-Díaz

DOI：10.1016/j.knosys.2019.07.025

原文链接

原文求助

摘要

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.

Keyword:

Recommender systems

Component-based development

Java

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

摘要

AI总结

期刊

机构

引用论文