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Knowledge Gathering from Social Media to Improve Marketing in Agri-food Sector

机译:通过社交媒体收集知识以改善农业食品领域的营销

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Nowadays many small and medium companies are interested in entering into foreign markets to establish a brand presence, sell their products and beat the competitors. Before making such a marketing decision, marketing experts can be guided by the traditional analysis of reports but also by the Web, through the analysis of social networks, blogs, forums, etc. These sources can provide real-time information about the perception that users have of specific brands and products. As a result, there are several tools that can extract interesting information from these unstructured data. In this paper, we propose an innovative knowledge extraction architecture realized through the integration of some existing tools. The aim is to retrieve the more frequent concepts from unstructured sources, suggest other links of articles and images, with multi-language feature so that the research is language independent. The architecture provides a knowledge base of a specific domain, which is used to suggest concepts related to the research, and to filter the results obtained from the elaboration of the unstructured sources. We present a case of study related to marketing in agri-food sector, in order to illustrate how the software works, the results obtained, their interpretation and the managerial implications.
机译:如今,许多中小型公司有兴趣进入国外市场以建立品牌形象,销售产品并击败竞争对手。在做出这样的营销决策之前,可以通过对社交网络,博客,论坛等的分析,以传统的报告分析为指导,以网络为指导,通过网络来指导营销专家。这些资源可以提供有关用户感知的实时信息。有特定的品牌和产品。结果,有几种工具可以从这些非结构化数据中提取有趣的信息。在本文中,我们提出了一种创新的知识提取体系结构,该体系结构通过集成一些现有工具而实现。目的是从非结构化来源中检索更常见的概念,建议文章和图像的其他链接,并具有多语言功能,从而使研究独立于语言。该体系结构提供了特定领域的知识库,该知识库用于建议与研究相关的概念,并过滤从详细阐述非结构化来源获得的结果。为了说明该软件如何工作,获得的结果,其解释和管理意义,我们在农业食品领域的营销方面进行了一项研究。

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