Abstract：Development of an Open Source Automated Library System with Book Recommedation System for Small Libraries This paper aims to develop an open source automated library system with book recommendation by using a combined method applied for small library systemsThis approach employs the machine learning of support-vector machines consisting of multiple features such as title similarityNDC category and bibliographic information of books based on loan record as learning dataThe bibliographic data are collected in the library database centerThis recommended method is based on the title similarity and bibliographic information of books such as authorcategorynumber of views and year of publicationThe various data used for the evaluation in Banpasao Chiangmai school was collected covering 2555 books in the database and 4612 books in the load recordThis 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 OPACOnline Public Access Catalog Onlinerepresented in our frameworkLibrary AutomationThis system is an open source automation library system for book recommendationCollection classificationBook recommendations by considering the similarity of the titleNDC category and other characteristicsRetrieval and IndexingUse data such as book informationauthorscategoriesviewing timesand publishing years as the basis of the recommendation methodIt mainly uses a method in machine learningcalled support-vector machnes to develop an automatic library system with book recommendation functionsThis method considers multiple characteristicssuch as title similarityNDC categoryand book information about books based on borrowing records