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Content Accessibility and Semantic Networks Processed on Foreign Natural Language Analysis

Keywords: Text mining , graph , Semantic network , Social network , Weak signals , Competitive Intelligence

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Abstract:

In this paper we present a methodology that makes it possible to mine a document collection from a domain withoutknowing the language in which the documents are written. We describe in detail a method, tools and results that can be usedwithin a digital library context for Science Watch and Competitive Intelligence. We consider a collection associated with theaquaculture domain written in Chinese and extracted from a digital library. Based on the original coding (UNICODE) of the dataand the tag marking the structure of the documents, we extract key elements (authors, phrases, etc.) from within the domain andanalyse them. The results are displayed in the form of graphs and networks. We extract people networks and semantic networksbefore examining their evolution over a period of several years. The principles developed in this paper can be applied to anylanguage.

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