RefSeer: A Citation Recommendation System

Citations are important in academic dissemination. To help researchers check the completeness of citations while authoring a paper, we introduce a citation recommendation system called RefSeer. RefSeer presents both topic-based global recommendations and citation-context-based local recommendations. Refseer uses documents in CiteSeerX for both its offline training and online recommendation. It is currently trained with over 5 million documents. Researchers can use this system while authoring papers to find related works to cite. It can also be used by reviewers to check the completeness of a paper’s references.

There has been much work on citation and paper recommendation systems. The goals of such research and systems are to provide authors insights into the existing relevant literature.

Sponsors:

This project is partially supported by the National Science Foundation.

References:
W. Huang, Z. Wu, C. Liang, P. Mitra, and C. Lee Giles. A Neural Probabilistic Model for Context Based Citation Recommendation. In the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI'15), 2015.
W. Huang, Z. Wu, P. Mitra, and C. Lee Giles. RefSeer: A Citation Recommendation System. In ACM/IEEE Joint Conference on Digital Libraries (JCDL'14), 2014.
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The Core Team

Prasenjit Mitra

Prasenjit Mitra

Associate Professor

Prof. Mitra leads the RefSeer project and is a co-PI on the next generation CiteSeerx project.

C. Lee Giles

C. Lee Giles

David Reese Professor

Prof. Giles co-leads the RefSeer project. He is a PI of the CiteSeerx project. He created CiteSeer in 1997 with Steve Lawrence and Kurt Bollacker while they were at the NEC Research Institute (now NEC Labs) in Princeton, New Jersey, USA. RefSeer is a functionality on top of the new generation CiteSeerx project.

Wenyi Huang

Wenyi Huang

Ph.D. Candidate

Wenyi currently looks after the algorithmic and technical development aspect of RefSeer.



Lior Rokach

Lior Rokach

Associate Professor

Information Systems and Software Engineering, Ben-Gurion University of the Negev.



With noted contributions from:

Saurabh Kataria

Saurabh Kataria

Former Technical Lead (Currently at PARC Xerox)

Saurabh used to develop the algorithmic and technical development aspect of RefSeer.

Cornelia Caragea

Cornelia Caragea

Assistant Professor

Computer Science and Engineering, University of North Texas.

Juan Pablo Fernandez Ramirez

Juan Pablo Fernández Ramírez

Software Engineer

Juan is a primary contributor to CiteSeerx project and helped port the CiteSeerx framework to RefSeer.



Dr. Qi He

Former Post Doc. (Currently at IBM, Almaden)

Qi He created the first prototype of the interface of the system.