RecPack:使用隐式反馈数据进行Top-N推荐的(另一个)实验工具包

L. Michiels, Robin Verachtert, Bart Goethals
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引用次数: 8

摘要

RecPack是一个易于使用,灵活和可扩展的工具包,用于隐式反馈数据的top-N推荐。它的目标是支持研究人员开发他们的推荐算法,从基于相似性的算法到深度学习算法,并允许正确、可重复和可重用的实验。在这个演示中,我们概述了这个包,并展示了研究人员在开发推荐算法时如何利用它。
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RecPack: An(other) Experimentation Toolkit for Top-N Recommendation using Implicit Feedback Data
RecPack is an easy-to-use, flexible and extensible toolkit for top-N recommendation with implicit feedback data. Its goal is to support researchers with the development of their recommendation algorithms, from similarity-based to deep learning algorithms, and allow for correct, reproducible and reusable experimentation. In this demo, we give an overview of the package and show how researchers can use it to their advantage when developing recommendation algorithms.
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