A Personal Ontology Model for Library Recommendation System

With the advent of information technology, library services are facing tremendous changes in the form of digitalization. In addition to the digitalization of library resources, personalized systems and recommendation systems are two of highly desirable services among library patrons. This study proposes a novel recommendation system based on analysis of loan records. In our system, we use the traditional cataloging scheme, such as the Library of Congress Classification (LCC), as the reference ontology and build personal ontology by mining interested subjects and relationships among subjects from patron's borrowing records. The proposed scheme can meet diversified demands of individual patron and provide patrons with a user-friendly interface to help them access needed information.

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