A review of enhancing online learning using graph-based data mining techniques
Author:
Publisher
Springer Science and Business Media LLC
Subject
Geometry and Topology,Theoretical Computer Science,Software
Link
https://link.springer.com/content/pdf/10.1007/s00500-022-07034-7.pdf
Reference76 articles.
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2. Akoglu L, McGlohon M, Faloutsos C (2010) Oddball: spotting anomalies in weighted graphs. In: Pacific-Asia conference on knowledge discovery and data mining, Springer, Berlin. https://doi.org/10.1007/978-3-642-13672-6_40
3. Akoglu L, Tong H, Koutra D (2015) Graph based anomaly detection and description: a survey. Data Min Knowl Discov 29(3):626–688. https://doi.org/10.1007/s10618-014-0365-y
4. Asghari A, Sohrabi MK, Yaghmaee F (2020) Online scheduling of dependent tasks of cloud’s workflows to enhance resource utilization and reduce the makespan using multiple reinforcement learning-based agents. Soft Comput 24:16177–16199. https://doi.org/10.1007/s00500-020-04931-7
5. Barnard L, Lan WY, To YM, Paton VO, Lai SL (2009) Measuring self-regulation in online and blended learning environments. Internet High Educ 12(1):1–6. https://doi.org/10.1016/j.iheduc.2008.10.005
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