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Combining article content and Web usage for literature recommendation in digital libraries

San‐Yih Hwang (Department of Information Management, National Sun Yat‐Sen University, Kaohsiung, Taiwan)
Shi‐Min Chuang (Department of Information Management, National Sun Yat‐Sen University, Kaohsiung, Taiwan)

Online Information Review

ISSN: 1468-4527

Article publication date: 1 August 2004

Abstract

In a large‐scale digital library, it is essential to recommend a small number of useful and related articles to users. In this paper, a literature recommendation framework for digital libraries is proposed that dynamically provides recommendations to an active user when browsing a new article. This framework extends our previous work that considers only Web usage data by utilizing content information of articles when making recommendations. Methods that make use of pure content data, pure Web usage data, and both content and usage data are developed and compared using the data collected from our university's electronic thesis and dissertation (ETD) system. The experimental results demonstrate that content data and usage data are complements of each other and hybrid methods that take into account of both types of information tend to achieve more accurate recommendations.

Keywords

Citation

Hwang, S. and Chuang, S. (2004), "Combining article content and Web usage for literature recommendation in digital libraries", Online Information Review, Vol. 28 No. 4, pp. 260-272. https://doi.org/10.1108/14684520410553750

Publisher

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Emerald Group Publishing Limited

Copyright © 2004, Emerald Group Publishing Limited