Unsupervised Anomaly Detection in Journal-Level Citation Networks-Reference-Cited by-同舟云学术

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Unsupervised Anomaly Detection in Journal-Level Citation Networks

Published:2020-08 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the ACM/IEEE Joint Conference on Digital Libraries in 2020
language:
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Author:

Jolly Baani Leen Kaur¹,Jain Lavina¹,Bera Debajyoti¹,Chakraborty Tanmoy¹

Affiliation:

1. Indraprastha Institute Information Technology, Delhi, New Delhi, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3383583.3398531

Reference35 articles.

1. Accessed April 7 2019. scimagojr.com. https://www.scimagojr.com/journalsearch.php?q=15107&tip=sid&clean=0. Accessed April 7 2019. scimagojr.com. https://www.scimagojr.com/journalsearch.php?q=15107&tip=sid&clean=0.

2. Accessed May 16 2020. Impact Factor. https://en.wikipedia.org/wiki/Impact_factor. Accessed May 16 2020. Impact Factor. https://en.wikipedia.org/wiki/Impact_factor.

3. Accessed May 16 2020. itsoc. https://www.itsoc.org/. Accessed May 16 2020. itsoc. https://www.itsoc.org/.

4. Accessed May 16 2020. Thomson Reuter. http://ipscience-help.thomsonreuters.com/incitesLiveJCR/JCRGroup/titleSuppressions.html. Accessed May 16 2020. Thomson Reuter. http://ipscience-help.thomsonreuters.com/incitesLiveJCR/JCRGroup/titleSuppressions.html.

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1. Graph Learning for Anomaly Analytics: Algorithms, Applications, and Challenges;ACM Transactions on Intelligent Systems and Technology;2023-02-16

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