China is an arising country, not only economicaly, but also scientifically. Being aware of the day to day evolution of this emerging country implicates to be able to read the local news, in Chinese langage. In this article we propose to use classical data-mining process tools in an original utilization for analyzing raw datas in order to procure knowledge for business intelligence (BI) application. The aim of this method is, not only to process Chinese datas, but also to create Intelligence by the analyze of the evolution over time of the interactions between specific object within the dataset (key-words, authors, affiliation, so on). The behavior of the environment in the analyzed field will thus be clearly legible throught a summarized representation of the raw datas, thus becoming knowledge. This work focus to provide a new theoretical framework technology for the retrieval information and the management of the associated knowledge, in a BI application. In this paper, we show how to use the data-mining tool and clusters analysis methodology to extract knowledge from a Chinese scientific database, without being able to read Chinese characters.

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In this paper the authors underline the increasing importance of Chinese scientific information. They compare the results of a request launched on Western and Chinese databases concerning Chinese scientific paper publication. Although Chinese scientists are having more and more visibility in international scientific journals, their publications in English are far fewer than those in Chinese. The difference is so drastic that it emphasizes the need for westerners (researchers and observers) to access and master the use of Chinese sources of information. The aim of this paper is to define the specificity of Chinese scientific information and also to present some primary results concerning the automatic analysis of Chinese writing. Our method uses a specific core language close to the point of view of the expert and his or her knowledge that will permit accurate information retrieval from a huge quantity of documents.