A Personalized Recommender System Based on Library Database

Chunyan Xu

Abstract


In recent years, the university libraries in China have acquired increasingly abundant electronic resources. However, the information silo phenomenon appears due to the lack of connection between university IT system and the community. Based on the book borrowing, favourite collection, comments and social relationship of students, this paper digs into the personalized interests of students, and promotes the design and implementation of a personalized recommender system. Specifically, the overall framework and recommender engine of the system were created based on the library data services. The modules in the system were also elaborated, and the recommendation results were verified by an offline test.

Keywords


Recommender system; personalized knowledge service; digital library

Full Text:

PDF


Copyright (c) 2017 Chunyan Xu


International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
Creative Commons License
Indexing:
Scopus logo Clarivate Analyatics ESCI logo EI Compendex logo IET Inspec logo DOAJ logo DBLP logo Learntechlib logo EBSCO logo Ulrich's logo Google Scholar logo MAS logo