Network-based approach to detect novelty of scholarly literature-Reference-Cited by-同舟云学术

Network-based approach to detect novelty of scholarly literature

Published:2018-01 Issue: Volume:422 Page:542-557
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Amplayo Reinald Kim,Hong SuLyn,Song Min

Funder

Ministry of Education of the Republic of Korea and the National Research Foundation of Korea

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

Reference33 articles.

1. Graph-based text classification: learn from your neighbors;Angelova,2006

2. A probabilistic framework for semi-supervised clustering;Basu,2004

3. Extracting complex biological events with rich graph-based feature sets;Bjorne,2009

4. Latent dirichlet allocation;Blei;J. Mach. Learn. Res.,2003

5. Scholarly Communication and Bibliometrics;Borgman;Ann. Rev. Inf. Sci. Technol. (ARIST),2002

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