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Title: A unified graph model for personalized query-oriented reference paper recommendation
Authors: Meng, F
Gao, D
Li, W 
Sun, XU
Hou, Y
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
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.
Keywords: Personalized reference paper recommendation
A unified graph-based recommendation model
ISBN: 978-1-4503-2263-8
DOI: 10.1145/2505515.2507831
Appears in Collections:Conference Paper

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