Visualisation of Relationships Among Library Users Based on Library Circulation Data

Abstract

A library has a large number of databases from which information can be extracted. But data retrieved is superficial and indicates only about the transactions of library. To predict and anticipate the future issue patterns such as what kind of books might be in demand more or what is the taste of majority of users, can only be found by mining the information from the data of library. The library circulation data does not indicate much about the relationship between the users based on the books got issued by them. The aim of this paper is to develop communities based on the issue patterns and find how many similar users are there and which type of books a  particular group of users prefer to read. So, the idea is to form a community-based on relationships among the library users and books and visualise the generated relationship through a graph to present the extracted information from the database more effectively. This is possible by finding the hidden relationships in data through community mining process, which has been done by identifying the relationship of users from library circulation data.

DOI: 10.14429/djlit.30.5