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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.