How to Use Methods of Data Mining in a Library: Example of University Library of Silesian University
Anna Janíková, Silesian University in Opava - Faculty of Philosophy and Science / Charles University in Prague - Faculty of Arts, Czech Republic
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There are many kinds of data, that libraries store. Every set of data originates from a different library activity. Sometimes we need stored data for further use. Sometimes we do not and when we do not know what to do with it, we just store it. Data just pile up with time. We spend manpower, capacity of servers and money to store it. We store it although we do not know, if we really need everything. We just can not delete it. Sometimes we use some of the data to create statistical reports. But what about the rest of it? Combination of methods of information technology can give us the answer. Data mining is a process, that allows us to do some powerful operations with our data. For example we can discover what kind of user is the most frequent in our library, which is useful for creating a model. We can also predict events, visualize data and detect potential abuse etc. Sometimes it is interesting to be able to see the data out of our database. This paper deals with the ways of seeing data in a different and still useful way. This poster focuses on the use of data mining with the data of University Library of Silesian University.
Author's professional CV
In 2008 Anna Janikova graduated from Information Studies and Librarianship at Department of Computer Science of Silesian University and gained her Master’s degree. She started working at the Department of Information Science of Institute of Computer Science as a teaching assistant. Her work is related to data mining and its use in libraries, project management, library information services and information and communicaton technologies. Since 2008 she is also a doctoral student at the Institute of Information Studies and Librarianship at the Faculty of Arts at Charles University in Prague. Her doctoral thesis deals with use of data mining in libraries.