流数据的实时推荐

Proceedings of the 9th ACM Conference on Recommender Systems Pub Date : 2015-09-16 DOI:10.1145/2792838.2792839

F. Hopfgartner, B. Kille, Tobias Heintz, R. Turrin

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引用次数: 8

摘要

本教程讨论了推荐系统研究领域的两个趋势主题，即A/B测试和流数据的实时推荐。以新闻领域为重点，参与者学习了如何在实时推荐系统和模拟环境中对基于流的推荐算法的性能进行基准测试。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Real-time Recommendation of Streamed Data

This tutorial addressed two trending topics in the field of recommender systems research, namely A/B testing and real-time recommendations of streamed data. Focusing on the news domain, participants learned how to benchmark the performance of stream-based recommendation algorithms in a live recommender system and in a simulated environment.

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Proceedings of the 9th ACM Conference on Recommender Systems

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