Nowadays many small and medium companies are interested in entering into foreign\nmarkets to establish a brand presence, sell their products and beat the competitors. Before\nmaking such a marketing decision, marketing experts can be guided by the traditional\nanalysis of reports but also by the Web, through the analysis of social networks, blogs,\nforums, etc. These sources can provide real-time information about the perception that\nusers have of specific brands and products. As a result, there are several tools that can\nextract interesting information from these unstructured data. In this paper, we propose an\ninnovative knowledge extraction architecture realized through the integration of some\nexisting tools. The aim is to retrieve the more frequent concepts from unstructured sources,\nsuggest other links of articles and images, with multi-language feature so that the research\nis language independent. The architecture provides a knowledge base of a specific domain,\nwhich is used to suggest concepts related to the research, and to filter the results obtained\nfrom the elaboration of the unstructured sources. We present a case of study related to\nmarketing in agri-food sector, in order to illustrate how the software works, the results\nobtained, their interpretation and the managerial implications.
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