Domain-Knowledge Driven Recommendation Method and Its Application

机译：领域知识驱动推荐方法及其应用

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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.

机译：为了解决当前推荐系统中领域知识匮乏，电子商务领域应用受限等问题，提出了一种基于二进制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，我们讨论了如何将领域知识与协作过滤相结合，并将其应用于二进制购买数据。超市数据集的实证结果表明，在三个常见的评价指标上，领域驱动的推荐方法优于其他推荐方法。

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《Fourth International Joint Conference on Computational Sciences and Optimization》|2011年|p.21-25|共5页
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Zhang Lingling; Zhang Xiaojie; Chen Quan; Zhu Zhengxiang; Shi Yong;
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中图分类计算技术、计算机技术;
关键词
collaborative filtering; domain knowledge; recommendation;

机译：协同过滤领域知识推荐;

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Domain-Knowledge Driven Recommendation Method and Its Application

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