In this article, we describe a hybrid recommender system (RS) in the artistic and cultural heritage area, which takes into account the activities on social media performed by the target user and her friends, and takes advantage of linked open data (LOD) sources. Concretely, the proposed RS (1) extracts information from Facebook by analyzing content generated by users and their friends; (2) performs disambiguation tasks through LOD tools; (3) profiles the active user as a social graph; (4) provides her with personalized suggestions of artistic and cultural resources in the surroundings of the user’s current location. The last point is performed by integrating collaborative filtering algorithms with semantic technologies in order to leverage LOD sources such as DBpedia and Europeana. Based on the recommended points of cultural interest, the proposed system is also able to suggest to the active user itineraries among them, which meet her preferences and needs and are sensitive to her physical and social contexts as well. Experimental results on real users showed the effectiveness of the different modules of the proposed recommender.

中文翻译：

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通过社交和链接的开放数据增强文化推荐

在本文中，我们描述了艺术和文化遗产领域的混合推荐系统 (RS)，该系统考虑了目标用户及其朋友在社交媒体上进行的活动，并利用链接的开放数据 (LOD) 源. 具体而言，所提出的 RS (1) 通过分析用户及其朋友生成的内容从 Facebook 中提取信息；(2) 通过LOD工具执行消歧任务；(3) 将活跃用户描述为社交图谱；(4) 向她提供用户当前所在位置周边艺术文化资源的个性化建议。最后一点是通过将协同过滤算法与语义技术集成来执行，以利用 DBpedia 和 Europeana 等 LOD 源。根据推荐的文化景点，提议的系统还能够向其中的活跃用户建议行程，这些行程满足她的偏好和需求，并且对她的身体和社会环境也很敏感。在真实用户上的实验结果表明了所提出推荐器不同模块的有效性。