Conference articles
Mining Complex Event Patterns in Computer Networks.
In:
Proc. ECML/PKDD Workshop on New Frontiers in Mining Complex Patterns.
Bristol, UK, 2012.
Dietmar Seipel, Philipp Neubeck, Stefan Köhler and Martin Atzmueller.
[BibTeX]
Miscellaneous
Modeling and Mining Ubiquitous Social Media.
2012.
[doi]
[BibTeX]
Journal articles
Mining Social Media: Key Players, Sentiments, and Communities.
WIREs: Data Mining and Knowledge Discovery, In Press, 2012.
Martin Atzmueller.
[BibTeX]
Conference articles
VIKAMINE - Open-Source Subgroup Discovery, Pattern Mining, and Analytics.
In:
Proc. ECML/PKDD 2012: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. accepted.
Springer Verlag, Heidelberg, Germany, 2012.
Martin Atzmueller and Florian Lemmerich.
[doi]
[BibTeX]
Conference proceedings
Proceedings MSM 2012: Workshop on Modeling Social Media - Collective Intelligence in Social Media.
ACM Press, New York, NY, USA, 2012.
Alvin Chin, Martin Atzmueller and Denis Helic.
[BibTeX]
Book chapters
Describing Locations using Tags and Images: Explorative Pattern Mining in Social Media.
In:
Modeling and Mining Ubiquitous Social Media.
Springer Verlag, Heidelberg, Germany, 2012.
Florian Lemmerich and Martin Atzmueller.
[doi]
[BibTeX]
Conference articles
Onto Collective Intelligence in Social Media: Exemplary Applications and Perspectives.
In:
Proc. 3rd International Workshop on Modeling Social Media (MSM 2012), Hypertext 2012.
ACM Press, New York, NY, USA, 2012.
Martin Atzmueller.
[BibTeX]
Book chapters
Data Mining, Validation and Collaborative Knowledge Capture.
In:
S. Brüggemann and C. d’Amato, editors,
Collaboration and the Semantic Web: Social Networks, Knowledge Networks, and Knowledge Resources, pages 149-167.
IGI Global, 2012.
Martin Atzmueller, Stephanie Beer and Frank Puppe.
[BibTeX]
Journal articles
Temporal data mining using shape space representations of time series.
Neurocomputing, 74(1–3):379 - 393, 2010.
Artificial Brains
Erich Fuchs, Thiemo Gruber, Helmuth Pree and Bernhard Sick.
[doi]
[abstract]
[BibTeX]
Subspace representations that preserve essential information of high-dimensional data may be advantageous for many reasons such as improved interpretability, overfitting avoidance, acceleration of machine learning techniques. In this article, we describe a new subspace representation of time series which we call polynomial shape space representation. This representation consists of optimal (in a least-squares sense) estimators of trend aspects of a time series such as average, slope, curve, change of curve, etc. The shape space representation of time series allows for a definition of a novel similarity measure for time series which we call shape space distance measure. Depending on the application, time series segmentation techniques can be applied to obtain a piecewise shape space representation of the time series in subsequent segments. In this article, we investigate the properties of the polynomial shape space representation and the shape space distance measure by means of some benchmark time series and discuss possible application scenarios in the field of temporal data mining.
Exploratory Pattern Mining on Social Media using Geo-References and Social Tagging Information.
International Journal of Web Science (Special Issue on Social Web Search and Mining), 2(1/2), 2013.
Martin Atzmueller and Florian Lemmerich.
[BibTeX]
Conference articles
On the Semantics of User Interaction in Social Media (Extended Abstract, Resubmission).
In:
Proc. LWA 2013 (KDML Special Track).
University of Bamberg, Bamberg, Germany, 2011.
Folke Mitzlaff, Martin Atzmueller, Gerd Stumme and Andreas Hotho.
[BibTeX]
On the Evolution of Contacts and Communities in Networks of Face-to-Face Proximity.
In:
Proc. IEEE CPSCom 2013.
IEEE Computer Society, Boston, MA, USA, 2013.
Mark Kibanov, Martin Atzmueller, Christoph Scholz and Gerd Stumme.
[BibTeX]
How Do People Link? Analysis of Contact Structures in Human Face-to-Face Proximity Networks.
In:
Proc. ASONAM 2013.
ACM Press, New York, NY, USA, 2013.
Christoph Scholz, Martin Atzmueller, Mark Kibanov and Gerd Stumme.
[BibTeX]
Book chapters
Mining Complex Event Patterns in Computer Networks.
In:
Postproceedings of the 1st Workshop on New Frontiers in Mining Complex Patterns (NFMCP 2012.
Springer Verlag, Heidelberg, Germany, 2013.
Dietmar Seipel, Stefan Köhler, Philipp Neubeck and Martin Atzmueller.
[BibTeX]
Journal articles
User-Relatedness and Community Structure in Social Interaction Networks.
CoRR/abs, 1309.3888, 2013.
Folke Mitzlaff, Martin Atzmueller, Dominik Benz, Andreas Hotho and Gerd Stumme.
[BibTeX]
Conference articles
Evolution of Contacts and Communities in Networks of Face-to-Face Proximity (Extended Abstract, Resubmission).
In:
Proc. LWA 2013 (KDML Special Track).
University of Bamberg, Bamberg, Germany, 2013.
Mark Kibanov, Martin Atzmueller, Christoph Scholz and Gerd Stumme.
[BibTeX]
Subgroup Analytics and Interactive Assessment on Ubiquitous Data.
In:
Proceedings of the International Workshop on Mining Ubiquitous and Social Environments (MUSE2013).
Prague, Czech Republic, 2013.
Martin Atzmueller and Juergen Mueller.
[BibTeX]
Miscellaneous
Conferator - a Social System for Conference and Contact Management.
Poster at INFORMATIK 2013. 2013.
Martin Atzmueller, Mark Kibanov, Christoph Scholz and Gerd Stumme.
[BibTeX]
Miscellaneous
Proceedings of the 2013 International Smart University Workshop (SmartU 2013).
2013.
[BibTeX]
Book chapters
Text Mining Scientific Papers: A Survey on FCA-Based Information Retrieval Research.
In:
P. Perner, editor,
Advances in Data Mining. Applications and Theoretical Aspects, pages 273-287.
Springer Berlin Heidelberg, 2012.
Jonas Poelmans, DmitryI. Ignatov, Stijn Viaene, Guido Dedene and SergeiO. Kuznetsov.
[doi]
[abstract]
[BibTeX]
Formal Concept Analysis (FCA) is an unsupervised clustering technique and many scientific papers are devoted to applying FCA in Information Retrieval (IR) research. We collected 103 papers published between 2003-2009 which mention FCA and information retrieval in the abstract, title or keywords. Using a prototype of our FCA-based toolset CORDIET, we converted the pdf-files containing the papers to plain text, indexed them with Lucene using a thesaurus containing terms related to FCA research and then created the concept lattice shown in this paper. We visualized, analyzed and explored the literature with concept lattices and discovered multiple interesting research streams in IR of which we give an extensive overview. The core contributions of this paper are the innovative application of FCA to the text mining of scientific papers and the survey of the FCA-based IR research.