Library User Behavior Patterns In Data Mining Research

In the age of digitization, when it comes to policy decision and decision-making in an organization, data collection and data mining are viewed as excellent reference resources. The purpose of library management is to meet readers? needs. Therefore, it is important for libraries to take the initiative to explore readers? requests and to provide them with the necessary materials. Library automation systems is not only the result of readers? satisfying their information needs but also the best evidence of how readers use library resource. In the process of data mining, the first step is to decide on the key subject of the research. My research studies borrowing history records of library automation systems of South West University Library. I use student databases as different department to build up a data warehouse by means of data cleaning and data transformation. I then analyze the data warehouse based on four parameters: collection, user, time, grade to make crisscross analyses which are cluster analysis, classification analysis, and association rules analysis. The final result of my analyses is the behaviors of how students use a library. It is a crucial and objective reference for the library to make management decisions including collection policy, library recommendations, budget allocation, and library-management.This research is the discussion excavates reader's behavior pattern using the data mining technology,揓nPan Information Management System? the history borrowing record take the SouthWest University library, South West University library User抯database, the booklist originates as the foundation data southwest, the performance data excavation technology explores the university reader's social group characteristic, and the performance data excavation achievement promotes the library the management and the service, and expected can cause the university library at the west big reader academic, in the knowledge absorption and the utilization acts a more positive role.The present paper plans the reader social group relations which explores to include:1. Book borrows common traits: Has the books which the similar interest reader usually borrows also to be able to be very similar, if borrows using the data mining technology the library books the common traits look?2. Book borrows order: The reader borrows the collection possibly to be able to borrow first basically borrows again thoroughly, how uses the data mining method to borrow the reader the library books?smooth characteristic to look?After we excavate reader's social group relations, hoped can utilize these social group relations and the data mining related technology achieves following goal:1. Attracts the reader to book borrowing: We discovered very many readers have never borrowed any book, how has to increase borrowing the reader population?2. Lifting Book抯borrowing rate: We discovered many books are not or are short extremely borrowed, how has to be able to憇ell?these books? 3. Promotes the reader loyalty: We discovered has very many readers only to borrow one, the pairs time no longer borrows, how has to promote reader's loyalty, enables the reader to borrow continually?4. Assistance books transcription purchase: when the Library buy books,the quantity of the buying book is often limited, but somewhat popular book reader must make an appointment very for a long time frequently can borrow, very many even is cannot borrow, therefore very many readers give up borrowing.How has to discover which is the popular book? Which this buys one?5. Promotion the library book conductivity: The expired also book to the library management, is a thorny work. Very many popular library books often expired only then returns, other readers must borrow the appointment to be very long can borrow.Therefore aims at the condition which the student exceeds the time limit to analyze, discovers exceeds the time limit frequently also the book special community, may beforehand make the prevention.6. Time series analysis: Uses the time series analysis regarding the open pipe time, discovers whether in each week, each month of even each season, every year the reader uses the library the time regularity, once the rule may discover, might lengthen or the reduction reference as the library open library time, such information especially in cold, summer vacation, will be more important, by the data mining technology obtained information, might the library抯decision-making unit provide the suitable manpower, simultaneously might also accept the open pipe regarding the library staff the time.