Based On Rough Set Data Mining Technology And Its Intelligent Software

With remarkable development in database technology and widely used database management system, more and more data are accumulated . There is lots of important information in the proliferated data, for the reason of better using the data, people want to analysis it in the higher-level way. The actual database management system has the efficient functions of data operations, such as: data storage, data query, data statistic etc. But, the database management system can not discovery the relationship and rule in the datum, and can not forecast the progress trend from actual datum. For the lack of the ability to find the knowledge concealed in the datum, leads to the phenomenon :Data Bang but the knowledge is poor. Data Mining can solve this problem. It is the process described as below: it extracts latent useful knowledge from mass, incomplete, noise, fuzzy and random datum.Knowledge discovery in Database (KDD) is a type of machine learning which enables the extraction of useful information from a set of raw data in a high-level format. Data Mining can bring markable benefits to business enterprise. It can be widely used in different commercial fields. The subject comes from Intel China Software Lab, Virtual Language Tutor Project. This project is to design a solution to help the language learners to accelerate the ability of language learning. I try to analysis the user's speech score and find the reason related with his score. In order to discover the concealed data stored in the database, I decided to use data mining and rough set theory to solve this problem. I designed the system according to the standard data mining process, which include: business object finding, data preparing, data mining and result analysising. Firstly, this paper introduces the VLT system and where the data come from. Secondly, it describes the background of data mining and some contents about it. Thirdly, it introduces the way of data mining using in the system: rough set, and puts forward the application model of rough set. At last, I summarize the functions performed and unperformed in this subject, and prospect for development of this subject.