领域知识驱动推荐方法及其应用

Lingling Zhang, Xiaojie Zhang, Quan Chen, Zhengxiang Zhu, Yong Shi
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引用次数: 3

摘要

针对当前推荐系统缺乏领域知识以及在电子商务领域应用有限的问题,提出了一种基于二值数据的领域驱动推荐方法。通过介绍领域知识的重要性及其在推荐中的应用,讨论了如何将领域知识与协同过滤相结合,并将其应用于二元采购数据。在超市数据集上的实证结果表明,领域驱动推荐方法在三个常用评价指标上优于其他推荐方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Domain-Knowledge Driven Recommendation Method and Its Application
In order to tackle the problems of current recommendation system, such as lack of domain knowledge and limited applications in e-commerce field, a domain-driven recommendation method based on binary data is proposed in this paper. By introducing the importance of domain knowledge and its application in recommendation, we discuss how to combine domain knowledge with collaborative filtering and apply it on binary purchasing data. Empirical result on supermarket dataset shows that domain-driven recommendation method outperforms other recommendation methods on three common evaluating indicators.
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