论文标题
通过情感意识的伪协会方法将不相交用户和项目关联来提出跨域建议
Making Cross-Domain Recommendations by Associating Disjoint Users and Items Through the Affective Aware Pseudo Association Method
论文作者
论文摘要
本文利用巧妙的基于文本的情感知识伪协会方法（AAPAM）将跨不同信息域的脱节用户和项目链接起来，并利用它们来制作基于跨域的基于内容和协作的过滤建议。本文表明，AAPAM方法可以无缝连接不同的信息域数据集，以充当一个没有任何其他跨域信息检索协议。除了提出跨域建议外，通过AAPAM加入来自不同信息域的数据集的好处是，它在提出偶然建议的同时消除了冷启动问题。
This paper utilizes an ingenious text-based affective aware pseudo association method (AAPAM) to link disjoint users and items across different information domains and leverage them to make cross-domain content-based and collaborative filtering recommendations. This paper demonstrates that the AAPAM method could seamlessly join different information domain datasets to act as one without any additional cross-domain information retrieval protocols. Besides making cross-domain recommendations, the benefit of joining datasets from different information domains through AAPAM is that it eradicates cold start issues while making serendipitous recommendations.
