A library recommender system based on a personal ontology model and collaborative filtering technique for English collections

Abstract

Purpose - The purpose of this paper is not only to design a more effective recommendation system for libraries, but also to eliminate many of the weaknesses found in the existing library recommender systems. Design/methodology/approach - A novel library recommender system was designed for English collections by integrating personal ontology model and collaborative filtering model with domain specification. Findings - The trend of the traditional library is evolving toward that of digital library. The personal ontology recommender (PORE) system offers a friendly user interface and provides several personalized services. Research limitations/implications This system is only implemented and tested in the Library of National Chung Using University in Taiwan. Originality/value - The paper demonstrates a good methodology to offer an active, effective, and personalized recommendation system for library patrons.