Deep Analysis of Data Mining Method in Personalized Information System of University Library

ABSTRACT

In order to discuss the application method and execution process of data mining in personalized information system establishment of university library, the thesis introduces existing condition of university library and insufficiency of the information service system. At the same time, data mining technology is introduced to simply describe the data mining process and introduce two top applications of the data mining technology in personalized library information system, namely student interest guidance quality and establishment of relevancy rule. Furthermore, more classical algorithms (FP-growth algorithm and K-mean clustering algorithm) are introduced in the data mining technology in detail. The data mining technology is a new data processing method. Nowadays, as for high flux reactor data analysis, data mining technology becomes more and more important in the construction process of personalized library information system.

Keywords:

University library, data mining, interest guiding, relevancy rule, Fp-growth algorithm, K-mean clustering algorithm.