Publications

US Patents Granted

1. Dmitriy Fradkin, Fabian Moerchen.  Condition monitoring with automatically generated error templates from log messages and sensor trends based on time semi-intervals. US 8423493.

2. Razvan Ioan Ionasec, Puneet Sharma, Bogdan Georgescu, Andrey Torzhkov, Fabian Moerchen, Gayle M. Wittenberg, Dmitriy Fradkin, Dorin Comaniciu. Multi-Component Heart and Aorta Modelling from High-Resolution MR and CT for Decision Support in Cardiac Disease. US 8527251.

3. Dmitriy Fradkin, Fabian Moerchen. Temporal pattern matching in large collections of log messages. US 9026550

4. Dmitriy Fradkin, Fabian Moerchen. Building a Failure-predictive Model from Message Sequences Generated by Complex Equipment or IT Systems. US 10162697 

5. Zhuang Wang, Fabian Moerchen, Dmitriy Fradkin. Log-based predictive maintenance using multiple-instance learning.  US 10579928B2

6. Dmitriy Fradkin, Volkmar Sterzing, Stefan Langer. Method for extracting an output data set. US 10803366

7. Dmitriy Fradkin, André Scholz, Matthias Loskyll, Georgia Olympia Brikis, Rakebul Hasan, Vladimir Lavrik, Alexander Storl. Method for generating a coherent representation for at least two log files. US 12072838B2 

8. Georgia Olympia Brikis, Dmitriy Fradkin, Vladimir Lavrik, Serghei Mogoreanu, André Scholz. Method for generating triples from log entries. US 12105749 

Thesis

• Dmitriy Fradkin. WITHIN-CLASS AND UNSUPERVISED CLUSTERING IMPROVE ACCURACY AND EXTRACT LOCAL STRUCTURE FOR SUPERVISED CLASSIFICATION. PhD Thesis, Rutgers, The State University of NJ, January 2006. pdf

Publications  (in reverse chronological order)

1. Unleashing the Power of Industrial Big Data through Scalable Manual Labeling.  Bruno P. Leao, Dmitriy Fradkin, Tu Lan, Jianhui Wang.  NeurIPS Data-Centric AI Workshop (2021). pdf 

2. Unsupervised Power System Event Detection and Classification Using Unlabeled PMU Data. Tu Lan, You Lin, Jianhui Wang, Bruno Leao and Dmitriy Fradkin. 2021 IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), October 2021. link pdf

3. Big Data Processing for Power Grid Event Detection. Bruno Paes Leao, Dmitriy Fradkin, Yubo Wang, and Sindhu Suresh. 2nd Workshop on Big Data Predictive Maintenance using Artificial Intelligence (BDPM_AI) at IEEE BigData, December 2020. link 

4. LogVis: Graph-Assisted Visual Analysis of Equipment Logs. Tugba Kulahcioglu, Dmitriy Fradkin, Ayse Parlak and Alexander Belkov. Visualization and Interaction for Ontologies and Linked Data (VOILA) Workshop, co-located with International Semantic Web Conference (ISWC), November 2020. pdf

5. Deep Reinforcement Learning for DER Cyber-Attack Mitigation. Ciaran Roberts, Sy-Toan Ngo, Alexandre Milesi, Sean Peisert, Daniel Arnold, Shammya S Saha, Anna Scaglione, Nathan G Johnson, Anton Kocheturov, Dmitriy Fradkin. IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm). November 2020. link pdf 

6. Multimodal Knowledge Graph for Deep Learning Papers and Code. Amar Viswanathan Kannan, Dmitriy Fradkin, Ioannis Akrotirianakis, Tugba Kulahcioglu, Arquimedes Canedo, Aditi Roy, Shih-Yuan Yu, Malawade Arnav, Mohammad Abdullah Al Faruque. ACM International Conference on Information and Knowledge Management (CIKM), October 2020. link

7. Diag2Graph: Representing Deep Learning Diagrams in Research Papers as Knowledge Graphs. Aditi Roy, Ioannis Akrotirianakis, Amar Viswanathan Kannan, Dmitriy Fradkin, Arquimedes Canedo, Kaushik Koneripalli, Tugba Kulahcioglu. IEEE International Conference on Image Processing (ICIP), October 2020. link

8. Incorporating Task Analysis in the Design of a Tool for a Complex and Exploratory Search Task. Tugba Kulahcioglu, Dmitriy Fradkin, Sridharan Palanivelu. ACM SIGIR Conference on Human Information Interaction and Retrieval (CHIIR), March 2017. link

9. An Efficient Pattern Mining Approach for Event Detection in Multivariate Temporal Data. Iyad Batal, Gregory Cooper, Dmitriy Fradkin, James Harrison, Fabian Moerchen, Milos Hauskrecht. Knowledge and Information Systems, 2016. link

10. Mining Sequential Patterns for Classification. Dmitriy Fradkin, Fabian Moerchen. Knowledge and Information Systems, 2015. link pdf appendix 

11. Log-based predictive maintenance. Ruben Sipos, Dmitriy Fradkin, Fabian Moerchen, Zhuang Wang.  International Conference on Knowledge Discovery and Data Mining (KDD), August 2014 link

12. Atlas of the clinical genetics of human dilated cardiomyopathy. J Haas et. al. European heart journal, 2014. link

13. Mining compressing sequential patterns. Hoang Thanh Lam, Fabian Moerchen, Dmitriy Fradkin, Toon Calders. Statistical Analysis and Data Mining: The ASA Data Science Journal 7 (1), 34-52, 2014 link

14. Zips: Mining compressing Sequential Patterns in Streams. Hoang Thanh Lam, Toon Calders, Jie Yang, Fabian Moerchen and Dmitriy Fradkin. Interactive Data Exploration and Analytics (IDEA) workshop at International Conference on Knowledge Discovery and Data Mining (KDD), August 2013. link pdf 

15. An Efficient Approach for Mining Recent Temporal Patterns. Iyad Batal, Dmitriy Fradkin,James Harrison, Fabian Moerchen, Milos Hauskrecht. International Conference on Knowledge Discovery and Data Mining (KDD), August 2012. link pdf 

16. Mining Compressing Sequential Patterns. Hoang Thanh Lam, Fabian Moerchen, Dmitriy Fradkin, Toon Calders. SIAM Conference on Data Mining (SDM), April 2012 link pdf 

17. Single Pass Text Classification by Direct Feature Weighting. H.H.Malik, D. Fradkin, F. Mörchen. Knowledge and Information Systems, 2011 link pdf

18. Margin-Closed Frequent Sequential Pattern Mining. D. Fradkin, F. Mörchen, F. In Proceedings of Useful Patterns Workshop (UP), KDD'10 link pdf 

19. Hierarchical document clustering using local patterns. H.H.Malik, J.R Kender, D. Fradkin, F. Mörchen. Data Mining and Knowledge Discovery 21(1), 2010 Springer link pdf

20. Robust mining of time intervals with semi-interval partial order patterns. F. Mörchen, D. Fradkin. In Proceedings SIAM Conference on Data Mining (SDM), 2010, pp. 315-326 link pdf 

21. Emerging Trend Prediction in Biomedical Literature. F. Moerchen, D. Fradkin, M. Dejori, B. Wachmann. Proceedings of AMIA Annual Symposium 2008: 485-489, November 2008 pdf 

22. Classifying Spend Transactions with Off-the-Shelf Learning Components. Saikat Mukherjee, Dmitriy Fradkin, Michael Roth.  Proceedings of the 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). November 2008. link pdf   Presentation

23. Clustering Inside Classes Improves Performance of Linear Classifiers. Dmitriy Fradkin.  Proceedings of the 20th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). November 2008: link pdf   Long version: pdf   Presentation

24. Anticipating Annotations and Emerging Trends in Biomedical Literature. F. Mörchen, M. Dejori, D. Fradkin, J. Etienne, B. Wachmann, M. Bundschus. Proceedings of KDD'08. link pdf  Presentation

25. Validation of Epidemiological Models: Chicken Epidemiology in the UK. Dmitriy Fradkin, Ilya Muchnik, Patrick Hermans, Kenton Morgan. Eds. J. Abello and G. Carmode. "Discrete Methods in Epidemiology", DIMACS Series in Discrete Mathematics and Theoretical Computer Science, volume 70, pp. 243-256, 2006. pdf

26. Support Vector Machines. Dmitriy Fradkin, Ilya Muchnik. Eds. J. Abello and G. Carmode. "Discrete Methods in Epidemiology", DIMACS Series in Discrete Mathematics and Theoretical Computer Science, volume 70, pp. 13-20, 2006. pdf. 

27. Prevalence of wet litter and the associated risk factors in broiler flocks in the United Kingdom. P. G. Hermans, D. Fradkin, I. B. Muchnik, and K. L. Morgan.  Veterinary Record, May 2006 (158):615 - 622. link

28. Simulated Entity Resolution by Diverse Means: DIMACS Work on the KDD Challenge of 2005. Andrei Anghelescu, Aynur Dayanik, Dmitriy Fradkin, Alex Genkin, Paul Kantor, David Lewis, David Madigan, Ilya Muchnik and Fred Roberts.  DIMACS Technical Report 2005-42: pdf

29. Machine Learning Methods in the Analysis of Lung Cancer Survival Data. Dmitriy Fradkin, Dona Schneider and Ilya Muchnik. DIMACS Technical Report 2005-35: ps.gz 

30. Bayesian Multinomial Logistic Regression for Author identification. David Madigan, Alexander Genkin, David D. Lewis and Dmitriy Fradkin. MaxEnt 2005: pdf. 

31. Author Identification on the Large Scale. David Madigan, Alexander Genkin, David D. Lewis, Shlomo Argamon, Dmitriy Fradkin and Li Ye.  Classification Society of North America: CSNA'05 pdf 

32. Methods for Learning Classifier Combinations: No Clear Winner. Dmitriy Fradkin and Paul Kantor. Proceedings of ACM Symposium on Applied Computing 2005, Information Access and Retrieval Track. March 2005: link pdf  (Presentation for SAC-IAR, March 2005)

33. Exploration Approaches to Adaptive Filtering. Dmitriy Fradkin and Micahel Littman.  DIMACS Technical Report 2005-01: ps.gz    Presentation for a Site Visit

34. DIMACS at the TREC 2004 Genomics Track. Aynur Dayanik, Dmitriy Fradkin, Alex Genkin, Paul Kantor, David D. Lewis, David Madigan, Vladimir Menkov. Proceedings of the 13th Text REtrieval Conference (TREC 2004): link pdf

35. Distinguishing Mislabeled Data from Correctly Labeled Data in Classifier Design. Sundara Venkataraman, Dimitris Metaxas, Dmitriy Fradkin, Casimir Kulikowski, Ilya Muchnik. Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (ICTAI). November 2004: link pdf  Presentation for ICTAI'04, Boca Raton, FL November 17, 2004 

36. A Design Space Approach to Analysis of Information Retrieval Adaptive Filtering Systems. Dmitriy Fradkin and Paul Kantor. Proceedings of the Thirteenth ACM Conference on Information and Knowledge Management (CIKM). November 2004.  link pdf  Presentation for CIKM'04, Washington, D.C. November 10, 2004 

37. A Study of K-Means Clustering for Improving Classification Accuracy of Multi-Class SVM. Dmitriy Fradkin and Ilya B. Muchnik.  DIMACS Technical Report 2004-02: ps.gz 

38. Clusters With Core-Tail Hierarchical Structure And Their Applications To Machine Learning Classification. Dmitriy Fradkin and Ilya B. Muchnik. Proceedings of KIMAS'03 Conference: link pdf   Presentation for KIMAS'03, Boston, MA. October 3, 2003 

39. Image Compression in Real-Time Multiprocessor Systems Using Divisive K-Means Clustering. Dmitriy Fradkin, Ilya B. Muchnik and Simon Streltsov. Proceedings of KIMAS'03 Conference: link pdf 

40. Experiments with Random Projections for Machine Learning. Dmitriy Fradkin and David Madigan. Proceedings of KDD'03 (edited for space): link pdf Longer version: pdf    Presentation at DIMACS Workshop on Discrete Metric Spaces and their Algorithmic Applications, Princeton, NJ, August 20 - 23, 2003; Poster for SIGKDD 

41. Monotonic Systems and Their Properties.  E. I. Kuznecov, I,B. Muchnik, L.V. Shvartzer. Translated from Russian by D. Fradkin. pdf

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