Every day researchers from all over the world have to filter the huge mass of existing research papers with the crucial aim of finding out useful publications related to their current work. In this paper we propose a research paper recommending algorithm based on the Citation Graph and random-walker properties. The PaperRank algorithm is able to assign a preference score to a set of documents contained in a digital library and linked one each other by bibliographic references. A data set of papers extracted by ACM Portal has been used for testing and very promising performances have been measured.
Gori, M., Pucci, A. (2006). Research Paper Recommender Systems: A Random-Walk Based Approach. In Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on (pp.778-781). New York : IEEE [10.1109/WI.2006.149].
Research Paper Recommender Systems: A Random-Walk Based Approach
GORI, MARCO;
2006-01-01
Abstract
Every day researchers from all over the world have to filter the huge mass of existing research papers with the crucial aim of finding out useful publications related to their current work. In this paper we propose a research paper recommending algorithm based on the Citation Graph and random-walker properties. The PaperRank algorithm is able to assign a preference score to a set of documents contained in a digital library and linked one each other by bibliographic references. A data set of papers extracted by ACM Portal has been used for testing and very promising performances have been measured.
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https://hdl.handle.net/11365/5737
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