Development of an Open Source Automated Library System with Book Recommedation System for Small Libraries

Abstract

© 2020 IEEE. This paper aims to develop an open source automated library system with book recommendation by using a combined method applied for small library systems. This approach employs the machine learning of support-vector machines consisting of multiple features such as title similarity, NDC category and bibliographic information of books based on loan record as learning data. The bibliographic data are collected in the library database center. This recommended method is based on the title similarity and bibliographic information of books such as author, category, number of views and year of publication. The various data used for the evaluation in Banpasao Chiangmai school was collected covering 2555 books in the database and 4612 books in the load record. This paper provides an effective solution for open source automated library systems suitable for small libraries where librarians can download and use our method using the OPAC (Online Public Access Catalog Online) represented in our framework.