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SMORE: Towards a semantic modeling for knowledge representation on social media

机译:SMORE:建立用于社交媒体上知识表示的语义建模

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摘要

This research presents SMORE, a semantic model for knowledge representation on social media. In order to provide recommendations, the model provides the elements for representing the content through the use of an ontological model and semantic techniques for the characterization and relationships between user profiles, products and social networks. In fact, with this model could be the basis of recommendation system based on social media data, and it could be exploited use by the recommendations on different products, which are stored in the Web and with similar characteristics between them. Moreover, SMORE represent the information related to user of the social networks in order to have a user characterization to be used for future recommendations in several domains. The semantic model has been evaluated with semantic data extracted from a trusted social network as, Twitter, obtaining the information specified by an expert in the field of marketing for recommendations in the automotive industry.
机译:这项研究提出了SMORE,一种用于社交媒体上知识表示的语义模型。为了提供建议,该模型通过使用本体模型和语义技术来表征用户概要文件,产品和社交网络之间的关系以及它们之间的关系,从而提供了表示内容的元素。实际上,该模型可以作为基于社交媒体数据的推荐系统的基础,并且可以被推荐用于存储在Web上且具有相似特征的不同产品上。而且,SMORE表示与社交网络的用户有关的信息,以便具有用户表征以用于多个领域中的未来推荐。语义模型已通过从Twitter等可信任的社交网络中提取的语义数据进行了评估,从而获得了行销领域的专家指定的信息,以供汽车行业推荐。

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