Flickr group recommendation based on tensor decomposition

Nan Zheng, Qiudan Li, Shengcai Liao, Leiming Zhang
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引用次数: 45

Abstract

Over the last few years, Flickr has gained massive popularity and groups in Flickr are one of the main ways for photo diffusion. However, the huge volume of groups brings troubles for users to decide which group to choose. In this paper, we propose a tensor decomposition-based group recommendation model to suggest groups to users which can help tackle this problem. The proposed model measures the latent associations between users and groups by considering both semantic tags and social relations. Experimental results show the usefulness of the proposed model.
基于张量分解的Flickr群组推荐
在过去的几年里,Flickr获得了巨大的人气,Flickr中的群组是照片传播的主要方式之一。然而,庞大的群组数量给用户选择哪个群组带来了麻烦。在本文中,我们提出了一个基于张量分解的群组推荐模型来向用户推荐群组,这有助于解决这个问题。该模型通过考虑语义标签和社会关系来度量用户和群体之间的潜在关联。实验结果表明了该模型的有效性。
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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