Towards an effective and unbiased ranking of scientific literature through mutual reinforcement
Published: Oct 29, 2012
Abstract
It is important to help researchers find valuable scientific papers from a large literature collection containing information of authors, papers and venues. Graph-based algorithms have been proposed to rank papers based on networks formed by citation and co-author relationships. This paper proposes a new graph-based ranking framework MutualRank that integrates mutual reinforcement relationships among networks of papers, researchers and venues to...
Paper Details
Title
Towards an effective and unbiased ranking of scientific literature through mutual reinforcement
Published Date
Oct 29, 2012
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