To read the full version of this content please select one of the options below:

Coauthorship network-based literature recommendation with topic model

San-Yih Hwang (Department of Information Management, National Sun Yat-sen University, Kaohsiung, Taiwan)
Chih-Ping Wei (Department of Information Management, National Taiwan University, Taipei, Taiwan)
Chien-Hsiang Lee (Department of Information Management, National Sun Yat-sen University, Kaohsiung, Taiwan)
Yu-Siang Chen (Department of Information Management, National Sun Yat-sen University, Kaohsiung, Taiwan)

Online Information Review

ISSN: 1468-4527

Publication date: 12 June 2017

Abstract

Purpose

The information needs of the users of literature database systems often come from the task at hand, which is short term and can be represented as a small number of articles. Previous works on recommending articles to satisfy users’ short-term interests have utilized article content, usage logs, and more recently, coauthorship networks. The usefulness of coauthorship has been demonstrated by some research works, which, however, tend to adopt a simple coauthorship network that records only the strength of coauthorships. The purpose of this paper is to enhance the effectiveness of coauthorship-based recommendation by incorporating scholars’ collaboration topics into the coauthorship network.

Design/methodology/approach

The authors propose a latent Dirichlet allocation (LDA)-coauthorship-network-based method that integrates topic information into the links of the coauthorship networks using LDA, and a task-focused technique is developed for recommending literature articles.

Findings

The experimental results using information systems journal articles show that the proposed method is more effective than the previous coauthorship network-based method over all scenarios examined. The authors further develop a hybrid method that combines the results of content-based and LDA-coauthorship-network-based recommendations. The resulting hybrid method achieves greater or comparable recommendation effectiveness under all scenarios when compared to the content-based method.

Originality/value

This paper makes two contributions. The authors first show that topic model is indeed useful and can be incorporated into the construction of coaurthoship-network to improve literature recommendation. The authors subsequently demonstrate that coauthorship-network-based and content-based recommendations are complementary in their hit article rank distributions, and then devise a hybrid recommendation method to further improve the effectiveness of literature recommendation.

Keywords

Acknowledgements

This work was partially supported in part by “Aim for the Top University Plan” of National Sun Yat-sen University in Taiwan and grants from Ministry of Science and Technology of Taiwan under Grant Nos MOST 104-2410-H-110 -039 -MY2 and MOST 104-2410-H-002-143-MY3.

Citation

Hwang, S.-Y., Wei, C.-P., Lee, C.-H. and Chen, Y.-S. (2017), "Coauthorship network-based literature recommendation with topic model", Online Information Review, Vol. 41 No. 3, pp. 318-336. https://doi.org/10.1108/OIR-06-2016-0166

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited