Recommender Systems Considering Context-restrictedness of Items

我们提出了考虑项目上下文限制的推荐系统。上下文受限项是在受限情况下可用的项。在本研究中，我们关注的是空间和时间情境。我们已经研究了空间和时间语境限制。实验结果表明，我们提出的方法分别使用真实餐厅数据集和地理标记推文数据集的有效性。我们还基于建议的系统实现了Web系统。

We proposed recommender systems considering context-restrictedness of items. Context-restricted items are the items which are available at restricted situations. In this research, we focus on spatial and temporal situations. We have studied about spatial and temporal context-restrictedness. Experimental results showed effectiveness of our proposed methods using real restaurant data sets and geo-tagged tweet data sets, respectively. We also implemented Web systems based on the proposed systems.