Decision Support System For Book Weeding

As the number of books and their information increases at a geometrical rate, book weeding and book selection play an increasingly important role in the process of book management. Traditional ways of book weeding focus on discarding those badly worn books and mainly rely on expert auditing, which is arduous and usually too subjective. Consequently, the speed and quality of traditional book weeding can not meet the needs of regarding book weeding as a conventional task in modern libraries. This thesis paper researches into the automation of book weeding, and proposes a decision support system for book weeding, which is constituted by three independent weeding strategies. In this way, book weeding can be carried out automatically by computers and its efficiency can be greatly improved. The main points of the thesis paper are as follows:Firstly, the author of the thesis paper proposes a half-life method for book weeding based on Huiwen book management system database. The half-life has been the key indicator of literature aging. Qualitative researches on half-life have already been very mature, and quantitative research and research on how literature growth rate influences half-life are the two main current research areas in the field of half-life study. In this research, the author applies those already mature half-life computational methods to book borrowing databases. More specifically, based on the circulation characteristics of library books, the author of this research develops a special half-life computational method, which can work out the aging degree of books in a certain classification and thus low value books can be picked out automatically according to their aging degree.Secondly, the author develops a method for rapid calculation of the utilization ratio of books, according to their borrowing frequency, duplicate copies and duration of existence. There have already existed some software for book weeding according to utilization ratio of books, and all these software highlight the importance of the circulation frequency of books. In this research, the decision support system for book weeding also pays great attention to the circulation frequency of books, and converts it into utilization ratio parameter. Due to the bulkiness and complexity of Huiwen book management system database, how to fast extract and handle the requisite data becomes the key point that should be taken into careful consideration. The utilization ratio of books plays a critical role in book weeding, especially in large-scale and unconventional book weeding. Experiment results indicate that it is time-consuming to extract intersectional data from multiple mega databases. In this case, it becomes necessary to establish a special graph and a specific index and use the method of "data extraction" for data transfer so as to improve efficiency.Thirdly, the author explores the computational method for working out the future lending possibility for current "zero lending books". Zero lending means that a book has never been lent within a specified period (usually a year or several years), which is a newly discovered universal phenomenon that exists in modern libraries. Weeding Zero lending books has always been the sticky issue in the automation of book weeding. The method proposed in this research is as follows:gaining experience and information from books with lending records, summarizing the time point when books are first lent, and estimating the future lending possibility for current zero lending books so as to provide a reference for book weeding.