High Impact Academic Paper Prediction Using Temporal and Topological Features

CIKM 2014
Pages: 491 - 498
Published: Nov 3, 2014
Abstract
Predicting promising academic papers is useful for a variety of parties, including researchers, universities, scientific councils, and policymakers. Researchers may benefit from such data to narrow down their reading list and focus on what will be important, and policymakers may use predictions to infer rising fields for a more strategic distribution of resources. This paper proposes a novel technique to predict a paper's future impact (i.e.,...
Paper Details
Title
High Impact Academic Paper Prediction Using Temporal and Topological Features
Published Date
Nov 3, 2014
Journal
Pages
491 - 498
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