Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/39874
Title: A unified graph model for personalized query-oriented reference paper recommendation
Authors: Meng, F
Gao, D
Li, W 
Sun, XU
Hou, Y
Keywords: Personalized reference paper recommendation
A unified graph-based recommendation model
Issue Date: 2013
Source: CIKM '13 Proceedings of the 22nd ACM International Conference on Conference on information & knowledge management, San Francisco, USA, October 27 - November 1, 2013, p. 1509-1512 How to cite?
Abstract: With the tremendous amount of research publications, it has become increasingly important to provide a researcher with a rapid and accurate recommendation of a list of reference papers about a research field or topic. In this paper, we propose a unified graph model that can easily incorporate various types of useful information (e.g., content, authorship, citation and collaboration networks etc.) for efficient recommendation. The proposed model not only allows to thoroughly explore how these types of information can be better combined, but also makes personalized query-oriented reference paper recommendation possible, which as far as we know is a new issue that has not been explicitly addressed in the past. The experiments have demonstrated the clear advantages of personalized recommendation over non-personalized recommendation.
URI: http://hdl.handle.net/10397/39874
ISBN: 978-1-4503-2263-8
DOI: 10.1145/2505515.2507831
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

7
Citations as of May 16, 2017

Page view(s)

31
Last Week
1
Last month
Checked on Aug 13, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.