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Enhancing cultural recommendations through social and linked open data

机译：通过社交和链接的开放数据增强文化推荐

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摘要

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.
机译：在本文中，我们描述了艺术和文化遗产地区的混合推荐系统（RS），其中考虑了目标用户及其朋友在社交媒体上进行的活动，并利用了链接开放数据（LOD）来源。具体而言，提出的RS（1）通过分析用户及其朋友产生的内容从Facebook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； （4）为她提供用户当前位置周围环境中的艺术和文化资源的个性化建议。最后一点是通过将协作过滤算法与语义技术集成在一起，以利用LOD来源（如DBpedia和Europeana）来执行的。基于推荐的文化兴趣点，所提出的系统还能够向活跃用户推荐其中的行程，这些行程可以满足她的喜好和需求，并且也对她的身体和社交环境敏感。在真实用户上的实验结果表明了建议推荐者的不同模块的有效性。

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