Research Interests

My research focuses on Big Data analysis, summarization and user-friendly visualization. In particular, I develop data clustering algorithms for fully automatic construction of user-friendly taxonomies of topics for various datasets including scientific papers. Also, I develop web components for visual exploration of the constructed taxonomies.

My work has been supported by the Swiss National Science Foundation, European Research Council and by the University of Fribourg.

Keywords

Clustering, community structure discovery, semantic web, ontology building, human-computer interaction, data visualization, clustering benchmarking, clustering quality measurement.

Jobs/Education

Projects at XI-Lab

While at UNIFR I implemented or contributed to the projects including:

Publications

  1. Artem Lutov, Mourad Khayati, and Philippe Cudré-Mauroux. “Accuracy Evaluation of Overlapping and Multi-Resolution Clustering Algorithms on Large Datasets.” In Proceedings of the 6th IEEE International Conference on Big Data and Smart Computing (BigComp 2019), 2019. Bibtex PDF
  2. Artem Lutov, Soheil Roshankish, Mourad Khayati, and Philippe Cudré-Mauroux. “StaTIX - Statistical Type Inference on Linked Data.” In IEEE International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018, 2253–62, 2018. Bibtex PDF
  3. Artem Lutov, Mourad Khayati, and Philippe Cudré-Mauroux. “Clubmark: A Parallel Isolation Framework for Benchmarking and Profiling Clustering Algorithms on NUMA Architectures.” In 2018 IEEE International Conference on Data Mining Workshops, ICDM Workshops, Singapore, Singapore, November 17-20, 2018, 1481–86, 2018. Bibtex Slides PDF
  4. Andrea Martini, Artem Lutov, Valerio Gemmetto, Andrii Magalich, Alessio Cardillo, Alex Constantin, Vasyl Palchykov, et al. “ScienceWISE: Topic Modeling over Scientific Literature Networks.” ArXiv e-Prints, 2016. Bibtex PDF