Personalised information services using a hybrid recommendation method based on usage frequency
Program: electronic library and information systems
ISSN: 0033-0337
Article publication date: 26 September 2008
Abstract
Purpose
This paper seeks to describe a personal recommendation service (PRS) involving an innovative hybrid recommendation method suitable for deployment in a large‐scale multimedia user environment.
Design/methodology/approach
The proposed hybrid method partitions content and user into segments and executes association rule mining, collaborative filtering, and contents popularity algorithms over various combinations of content partitions and user groups. The process results in recommended content for end‐users based on the linear combination of candidate data sets.
Findings
This study reveals that: the use of usage frequency is an effective way to analyse user's behaviour patterns and their selection of content; the partitioning of content and users into meaningful groups and the identification of optimal parameter values of constituent recommendation methods, yields successful results in the implementation; the hybrid method performs better than any constituent methods in most evaluation metrics.
Practical implications
The PRS system serves as a useful reference for electronic libraries or information centres considering the development of personalised information services.
Originality/value
The PRS system is designed and implemented to work efficiently in the large‐scale multimedia user environment. It can also be applied to small and medium‐scale environments or mobile platforms.
Keywords
Citation
Kim, Y. and Gyo Chung, M. (2008), "Personalised information services using a hybrid recommendation method based on usage frequency", Program: electronic library and information systems, Vol. 42 No. 4, pp. 436-447. https://doi.org/10.1108/00330330810912106
Publisher
:Emerald Group Publishing Limited
Copyright © 2008, Emerald Group Publishing Limited