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Selected articles from the Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019).

Zhe He1, Cui Tao2, Jiang Bian3

  • 1School of Information, College of Communication and Information, Florida State University, 142 Collegiate Loop, Tallahassee, FL, 32306-2100, USA. zhe@fsu.edu.

BMC Medical Informatics and Decision Making
|December 15, 2020
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Summary

The Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019) focused on Knowledge Graphs, Ontology-Powered Analytics, and Deep Learning. Seven research articles from the workshop are summarized, advancing semantic data mining and analytics.

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Area of Science:

  • Data Science
  • Artificial Intelligence
  • Semantic Web Technologies

Background:

  • The Fourth International Workshop on Semantics-Powered Data Mining and Analytics (SEPDA 2019) was held alongside the 18th International Semantic Web Conference (ISWC 2019).
  • The workshop addressed the growing need for advanced data mining and analytics techniques powered by semantic technologies.
  • This supplement issue features research presented at SEPDA 2019.

Purpose of the Study:

  • To summarize the key themes and contributions of SEPDA 2019.
  • To introduce seven selected research articles from the workshop.
  • To highlight advancements in Knowledge Graph, Ontology-Powered Analytics, and Deep Learning for data mining.

Main Methods:

  • The workshop proceedings were reviewed to identify key research areas.
  • Seven representative articles were selected for inclusion in this supplement.
  • The selected articles cover diverse applications of semantic technologies in data mining.

Main Results:

  • The workshop successfully brought together researchers in semantics-powered data mining.
  • The featured articles demonstrate novel approaches in Knowledge Graph construction and utilization.
  • Significant progress was shown in Ontology-Powered Analytics and the application of Deep Learning in semantic data analysis.

Conclusions:

  • SEPDA 2019 highlighted the critical role of semantics in modern data mining and analytics.
  • The research presented offers valuable insights and methodologies for leveraging semantic data.
  • Future work should continue to explore the intersection of semantic web technologies, AI, and data science.