Study Of Some Questions Of Building MSMiner

The MSMiner system is a multi-strategy data mining platform that developed by Intelligent Science Laboratory of Institute of Computing Technology, Chinese Academy of Sciences. This paper first introduces the development history of data mining software, pointes out the strong points and flaws of these software in each phases. To display the strong points of MSMiner, I also compare these software with MSMiner. After introducing the architecture of MSMiner and some important technologies used in this system, functions of each module were described. Then I study how to build up an object oriented model of metadata, and discuss the strongpoints of it, and how to make metadata to be a core of MSMiner. Next, this paper explains the importance of ETL in data warehouse and talks about some key questions that must be considered in ETL module's designing. All the questions that have been discussed give a general idea of building up data warehouse, and building up an excellent data warehouse is the important foundation of online analytical processing and data mining. Finally, I realize and optimize two algorithms: apriori algorithm and back-propagation algorithm. From a lot of experiments and some application of the two algorithms, a conclusion can be drawn: the optimized algorithms have better efficiency and accuracy than original ones in large data sets.