A unified graph model for personalized query-oriented reference paper recommendation

Fanqi Meng, Dehong Gao, Wenjie Li, Xu Sun, Yuexian Hou

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

36 Citations (Scopus)

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.
Original languageEnglish
Title of host publicationCIKM 2013 - Proceedings of the 22nd ACM International Conference on Information and Knowledge Management
Pages1509-1512
Number of pages4
DOIs
Publication statusPublished - 11 Dec 2013
Event22nd ACM International Conference on Information and Knowledge Management, CIKM 2013 - San Francisco, CA, United States
Duration: 27 Oct 20131 Nov 2013

Conference

Conference22nd ACM International Conference on Information and Knowledge Management, CIKM 2013
CountryUnited States
CitySan Francisco, CA
Period27/10/131/11/13

Keywords

  • A unified graph-based recommendation model
  • Personalized reference paper recommendation

ASJC Scopus subject areas

  • Decision Sciences(all)
  • Business, Management and Accounting(all)

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