Implicit Multi-Feature Learning for Dynamic Time Series Prediction of the Impact of Institutions

Implicit Multi-Feature Learning for Dynamic Time Series Prediction of the Impact of Institutions

Predicting the impact of research institutions is an important tool for decision makers, such as resource allocation for funding bodies. Despite significant effort of adopting quantitative indicators to measure the impact of research institutions, little is known that how the impact of institutions...

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Bibliographic Details
Main Authors: Xiaomei Bai, Fuli Zhang, Jie Hou, Feng Xia, Amr Tolba, Elsayed Elashkar
Format: Article
Language:English
Published: IEEE 2017-01-01
Series:IEEE Access
Subjects:
Scientific impact
prediction
feature selection
machine learning
scientometrics
Online Access:https://ieeexplore.ieee.org/document/8010278/

Internet

https://ieeexplore.ieee.org/document/8010278/

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