Matthias Carnein


I am a 29-year-old PhD candidate at the University of Münster, Germany where I work at the Information Systems and Statistics Group. My research focuses on methods used in data science including the analysis of data streams and clustering with applications in market segmentation and customer relationship management.

Education

since 03/2016
PhD
PhD candidate in Information Systems at the University of Münster, Germany.

Large parts of my PhD were carried out in collaboration with Arvato, a subsidiary of Bertelsmann. A few news articles about my research and the collaboration are available at:
10/2013 – 09/2015
Master of Science
Master Studies in Information Systems at the University of Münster, Germany
10/2010 – 09/2013
Bachelor of Science
Bachelor Studies in Information Systems at the University of Münster, Germany

Positions

since 03/2016
Research Assistant
Information Systems and Statistics Group at the University of Münster, Germany
04/2017 – 12/2017
Lecturer
Certificate programme ‘Data Science’ at the Münster University Continuing Education (WWU Weiterbildung)
01/2016 – 02/2016
Graduate Student Assistant
Information Systems and Statistics Group at the University of Münster, Germany
04/2014 – 12/2015
Graduate Student Assistant
IT Security Group at the University of Münster, Germany
11/2012 – 03/2014
Student Assistant
Information Systems and Information Management Group at the University of Münster, Germany

Conferences & Events

September 2019 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD ’19) in Würzburg, Germany
July 2019 21st IEEE Conference on Business Informatics (CBI ’19) in Moscow, Russia, Best Paper Award
April 2019 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD ’19) in Macau, China
February 2019 Visiting scholar at the University of Waikato in Hamilton, New Zealand, Marie Skłodowska-Curie Fellowship
January 2019 Visiting scholar at the Queensland University of Technology in Brisbane, Australia, Marie Skłodowska-Curie Fellowship
July 2018 1st Metaheuristics Summer School (MESS) in Sicily, Italy
November 2017 36th International Conference on Conceptual Modeling (ER ’17) in Valencia, Spain
August 2017 German-Brazilian Workshop on Information Systems in Logistics and Production Engineering in Recife, Brazil
May 2017 ACM International Conference on Computing Frontiers (CF ’17) in Siena, Italy
March 2017 17th Conference on Database Systems for Business, Technology, and Web (BTW ’17) in Stuttgart, Germany
9th International Conference on Evolutionary Multi-Criterion Optimization (EMO ’17) in Münster, Germany
June 2016 11th Madrid UPM Advanced Statistics and Data Mining Summer School in Madrid, Spain
Februrary 2016
IS&T Electronic Imaging: Media Watermarking, Security, and Forensics (EI ’16) in San Francisco, USA
November 2015 7th IEEE International Workshop on Information Forensics and Security (WIFS ’15) in Rome, Italy
June 2014 2nd ACM Workshop on Information Hiding and Multimedia Security (IH & MMSec ’14) in Salzburg, Austria

Teaching

Winter Term 19/20
  • Data Analytics I (Master Lecture)
Summer Term 19
  • Auto-ML (Master Seminar)
  • Data Analytics II: Support Vector Machines (Master Lecture)
  • Dialogue Act Classification in the CRM Context (Master Thesis)
Winter Term 18/19
  • Introduction to Information Systems: Statistics / Analytics (Bachelor Lecture)
Summer Term 18
  • Text Mining to Prioritize Maintenance Tasks in Agile Software Projects (Master Thesis)
  • Identification of Disease Candidates based on Medical History (Master Thesis)
  • Data Analytics II: Support Vector Machines (Master Lecture)
  • Chat Bot for the Examination Office (Bachelor Project Seminar) [News Article] [News Article] [News Article] [News Article]
Winter Term 17/18
  • Customer Service at HILTI (Master Project Seminar)
  • Statistical Methods in Retail (Master Seminar)
  • Introduction to Information Systems: Statistics / Analytics (Bachelor Lecture)
  • Data Analytics I: R-Course (Master Lecture)
  • Image Segmentation for the Microstructural Analysis of Engine Materials (Master Thesis)
Summer Term 17
  • Data Analytics II: Support Vector Machines (Master Lecture)
Winter Term 16/17
  • Stream Clustering (Master Seminar)
  • Applied Machine Learning (Master Seminar)
  • Tech-enabled Omni-channel CRM (Bachelor Project Seminar)
  • Data Analytics I: Stream Clustering (Master Lecture)
  • Empirical Comparison of Stream Clustering Algorithms (Bachelor Thesis)
  • Applied Customer Base Analysis in a Noncontractual Setting Based on Transactional Data (Master Thesis)
Summer Term 16
  • Data Analytics II: Support Vector Machines (Master Lecture)

Tools & Software

MOA /
confStream
I am a contributor to the Massive Online Analysis (MOA) framework. MOA is the most popular framework for stream data mining. My contribution is currently maintained as a fork and implements the confStream algorithm as proposed in our ECML PKDD ’19 paper.
stream I am a contributor to the popular R-Package ‘stream’ which implements various functions and algorithms to cluster data streams. The package was used for our ER ’17 paper, CF ’17 paper, BISE article and Big Data Research article.
streamMOA I am a contributor to the R-Package ‘streamMOA’ which interfaces the stream clustering algorithms available in the Massive Online Analysis (MOA) library. The package was used for our CF ’17 paper, BISE article and Big Data Research article.
evoStream An evolutionary stream clustering algorithm. The algorithm is able to utilize the idle time in a stream in order to incrementally improve the clustering result. The package was used for our Big Data Research article.
userStream Implementation of a stream clustering algorithm applicable to customer segmentation. The algorithm allows to identify and track segments of similar customers over time as proposed in our PAKDD ’19 paper.
textClust A stream clustering algorithm which can identify and track topics in a stream of texts as proposed in our ER ’17 paper.
Customer Service
Monitor
A tool to analyse customer service on Social Media. The tool allows to automatically determine how often and frequently companies respond to questions on facebook and twitter. The tool was used for our BTW ’17 paper.
jpegToolbox An R-Package that provides various implementations of the JPEG image compression algorithm. Most importantly, an interface to the popular libjpeg library is available. The package ships with pre-compiled libraries of libjpeg versions 6b, 8d and 9a for Windows. In addition, the entire lossy compression pipeline is implemented in R for easy debugging as well as in C++ with interfaces to R for faster computation speed. The implementations were used for our EI ’16 paper and WIFS ’15 paper.

Publications

Carnein M, Trautmann H, Bifet A and Pfahringer B (2019), "Towards Automated Configuration of Stream Clustering Algorithms", In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD '19).
[Paper] [Poster] [BibTeX] [Details]
@inproceedings{ECMLPKDD19,
	author = {Matthias Carnein and Heike Trautmann and Albert Bifet and Bernhard Pfahringer},
	title = {Towards Automated Configuration of Stream Clustering Algorithms},
	booktitle = {Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD '19)},
	year = {2019}
}
Carnein M, Homann L, Trautmann H and Vossen G (2019), "A Recommender System Based on Omni-Channel Customer Data", In Proceedings of the 21st IEEE Conference on Business Informatics (CBI '19). Moscow, Russia, Best Paper Award
[Paper] [Presentation] [BibTeX]
@inproceedings{CBI19,
  author = {Matthias Carnein and Leschek Homann and Heike Trautmann and Gottfried Vossen},
  title = {A Recommender System Based on Omni-Channel Customer Data},
  booktitle = {21st IEEE Conference on International Conference on Business Informatics (CBI '19)},
  year = {2019}
}
Carnein M and Trautmann H (2019), "Customer Segmentation Based on Transactional Data Using Stream Clustering", In Advances in Knowledge Discovery and Data Mining. Cham, pp. 280-292. Springer International Publishing.
[Paper] [Presentation] [BibTeX] [Details] [DOI] [News Article]
@inproceedings{PAKDD19,
  author = {Matthias Carnein and Heike Trautmann},
  editor = {Yang, Qiang and Zhou, Zhi-Hua and Gong, Zhiguo and Zhang, Min-Ling and Huang, Sheng-Jun},
  title = {Customer Segmentation Based on Transactional Data Using Stream Clustering},
  booktitle = {Advances in Knowledge Discovery and Data Mining},
  publisher = {Springer International Publishing},
  year = {2019},
  pages = {280--292},
  doi = {10.1007/978-3-030-16148-4_22}
}
Carnein M and Trautmann H (2019), "Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms", Business & Information Systems Engineering (BISE).
[Paper] [BibTeX] [DOI] [Details]
@article{BISE19,
  author = {Matthias Carnein and Heike Trautmann},
  title = {Optimizing Data Stream Representation: An Extensive Survey on Stream Clustering Algorithms},
  journal = {Business & Information Systems Engineering (BISE)},
  year = {2019},
  doi = {10.1007/s12599-019-00576-5}
}
Carnein M and Trautmann H (2018), "evoStream - Evolutionary Stream Clustering Utilizing Idle Times", Big Data Research., May, 2018. Vol. 14, pp. 101 - 111.
[Paper] [BibTeX] [DOI] [Details]
@article{BDR18,
  author = {Matthias Carnein and Heike Trautmann},
  title = {evoStream -- Evolutionary Stream Clustering Utilizing Idle Times},
  journal = {Big Data Research},
  year = {2018},
  volume = {14},
  pages = {101 - 111},
  doi = {10.1016/j.bdr.2018.05.005}
}
Carnein M., Assenmacher D. and Trautmann H. (2017), ‘Stream Clustering of Chat Messages with Applications to Twitch Streams’. In: Proceedings of the 36th International Conference on Conceptual Modeling (ER '17). Valencia, Spain, 2017, pp. 79-88.
[Paper] [Presentation] [BibTeX] [DOI] [Details]
@InProceedings{ER17Twitch,
  author    = {Carnein, Matthias and Assenmacher, Dennis and Trautmann, Heike},
  title     = {Stream Clustering of Chat Messages with Applications to Twitch Streams},
  booktitle = {Proceedings of the 36th International Conference on Conceptual Modeling (ER '17)},
  year      = {2017},
  publisher = {Springer International Publishing},
  location  = {Valencia, Spain},
  isbn      = {978-3-319-70625-2},
  pages     = {79--88},
  doi       = {10.1007/978-3-319-70625-2_8},
}
Carnein M, Heuchert M, Homann L, Trautmann H, Vossen G, Becker J and Kraume K (2017), ‘Towards Efficient and Informative Omni-Channel Customer Relationship Management’. In: Proceedings of the 36th International Conference on Conceptual Modeling (ER '17). Valencia, Spain, 2017 pp. 69-78.
[Paper] [BibTeX] [DOI]
@InProceedings{ER17Omni,
  author    = {Carnein, Matthias and Heuchert, Markus and Homann, Leschek and Trautmann, Heike and Vossen, Gottfried and Becker, Jörg and Kraume, Karsten},
  title     = {Towards Efficient and Informative Omni-Channel Customer Relationship Management},
  booktitle = {Proceedings of the 36th International Conference on Conceptual Modeling (ER '17)},
  year      = {2017},
  publisher = {Springer International Publishing},
  location  = {Valencia, Spain},
  isbn      = {978-3-319-70625-2},
  pages     = {69--78},
  doi       = {10.1007/978-3-319-70625-2_7},
}
Carnein, M., Assenmacher, D. and Trautmann, H. ‘An Empirical Comparison of Stream Clustering Algorithms’. In: Proceedings of the ACM International Conference on Computing Frontiers (CF ’17). Siena, Italy, 2017, pp. 361–365.
[Paper] [Presentation] [BibTeX] [DOI]
@InProceedings{CF17,
  author    = {Matthias Carnein AND Dennis Assenmacher AND Heike Trautmann},
  title     = {An Empirical Comparison of Stream Clustering Algorithms},
  booktitle = {Proceedings of the ACM International Conference on Computing Frontiers (CF '17)},
  year      = {2017},
  publisher = {ACM},
  location  = {Siena, Italy},
  pages     = {361 -- 365},
  doi       = {10.1145/3075564.3078887},
}
Carnein, M., Homann, L., Trautmann, H., Vossen, G. and Kraume, K. ‘Customer Service in Social Media: An Empirical Study of the Airline Industry’. In: Proceedings of the 17th Conference on Database Systems for Business, Technology, and Web (BTW ’17). Stuttgart, Germany, 2017, pp. 33-40.
[Paper] [Presentation] [BibTeX] [Publisher] [Website] [News Article]
@InProceedings{BTW17,
  author    = {Matthias Carnein and Leschek Homann and Heike Trautmann and Gottfried Vossen and Karsten Kraume},
  title     = {Customer Service in Social Media: An Empirical Study of the Airline Industry},
  booktitle = {Proceedings of the 17th Conference on Database Systems for Business, Technology, and Web (BTW '17)},
  year      = {2017},
  location  = {Stuttgart, Germany},
  isbn      = {978-3-88579-660-2},
  pages     = {33--40},
}
Trautmann, H., Vossen, G., Homann, L., Carnein, M. and Kraume, K. Challenges of Data Management and Analytics in Omni-Channel CRM. Tech. rep. 28. Münster, Germany: European Research Center for Information Systems, 2017.
[Paper] [BibTeX] [Publisher]
@TechReport{ERCISWP17,
  author      = {Heike Trautmann and Gottfried Vossen and Leschek Homann and Matthias Carnein and Karsten Kraume},
  title       = {Challenges of Data Management and Analytics in Omni-Channel CRM},
  institution = {European Research Center for Information Systems},
  year        = {2017},
  address     = {Münster, Germany},
  editor      = {Jörg Becker and Klaus Backhaus and Martin Dugas and Bernd Hellingrath and Thomas Hoeren and Stefan Klein and Herbert Kuchen and Heike Trautmann and Gottfried Vossen},
  series      = {ERCIS Working Papers},
  volume      = {28},
}
Carnein, M., Schöttle, P. and Böhme, R. ‘Telltale Watermarks for Counting JPEG Compressions’. In: Proceedings of IS&T Electronic Imaging: Media Watermarking, Security, and Forensics (EI ’16). 8. San Francisco, CA, 2016, pp. 1-10.
[Paper] [Presentation] [BibTeX] [DOI]
@InProceedings{EI16,
  author    = {Matthias Carnein and Pascal Schöttle and Rainer Böhme},
  title     = {Telltale Watermarks for Counting JPEG Compressions},
  booktitle = {Proceedings of IS\&T Electronic Imaging: Media Watermarking, Security, and Forensics (EI’16)},
  year      = {2016},
  number    = {8},
  location  = {San Francisco, CA},
  pages     = {1--10},
  doi       = {10.2352/ISSN.2470-1173.2016.8.MWSF-072},
  issn      = {2470-1173},
}
Carnein, M., Schöttle, P. and Böhme, R. ‘Forensics of High-Quality JPEG Images with Color Subsampling’. In: Proceedings of the 7th IEEE International Workshop on Information Forensics and Security (WIFS '15). Rome, Italy, Nov. 2015, pp. 1-6.
[Paper] [Presentation] [BibTeX] [DOI]
@InProceedings{WIFS15,
  author    = {Matthias Carnein and Pascal Schöttle and Rainer Böhme},
  title     = {Forensics of High-Quality JPEG Images with Color Subsampling},
  booktitle = {Proceedings of the 7th IEEE International Workshop on Information Forensics and Security (WIFS '15)},
  year      = {2015},
  publisher = {IEEE},
  location  = {Rome, Italy},
  month     = {11},
  pages     = {1--6},
  doi       = {10.1109/WIFS.2015.7368556},
}
Carnein, M., Schöttle, P. and Böhme, R. ‘Predictable Rain? Steganalysis of Public-key Steganography Using Wet Paper Codes’. In: Proceedings of the 2nd ACM Workshop on Information Hiding and Multimedia Security (IH & MMSec ’14). Salzburg, Austria, 2014, pp. 97-108.
[Paper] [Presentation] [BibTeX] [DOI]
@InProceedings{IH14,
  author    = {Matthias Carnein and Pascal Schöttle and Rainer Böhme},
  title     = {Predictable Rain? Steganalysis of Public-key Steganography Using Wet Paper Codes},
  booktitle = {Proceedings of the 2nd ACM Workshop on Information Hiding and Multimedia Security (IH \& MMSec '14)},
  year      = {2014},
  publisher = {ACM},
  location  = {Salzburg, Austria},
  isbn      = {978-1-4503-2647-6},
  pages     = {97--108},
  doi       = {10.1145/2600918.2600942},
}
Carnein, M., Quiring, E., Haack, A., Möhring, A. and Becker, J. ‘Laiengerechte Erzeugung von 3D-Animationen am Beispiel von textuellen Unfallbeschreibungen’. In: Proceedings of the 17th International Legal Informatics Symposium (IRIS ’14). Salzburg, Austria, 2014, pp. 473-480.
[BibTeX] [URL]
@InProceedings{IRIS14,
  author    = {Matthias Carnein and Erwin Quiring and Andreas Haack and Andreas Möhring and Jörg Becker},
  title     = {Laiengerechte Erzeugung von 3D-Animationen am Beispiel von textuellen Unfallbeschreibungen},
  booktitle = {Proceedings of the 17th International Legal Informatics Symposium (IRIS '14)},
  year      = {2014},
  pages     = {473--480},
  url       = {http://jusletter-it.weblaw.ch/issues/2014/IRIS/2544.html},
  address   = {Salzburg, Austria},
}