Details

Veröffentlicht: Montag, 12. Oktober 2015 12:51

Acknowlegements:

Bei Inanspruchnahme von HPC-Computetime: "The authors gratefully acknowledge the GWK support for funding this project by providing computing time through the Center for Information Services and HPC (ZIH) at TU Dresden on HRSK-II."

Zu ScaDS-Funding: [Furthermore, t]This work was supported by the German Federal Ministry of Education and Research (BMBF, 01/S18026A-F) by funding the competence center for Big Data and AI “ScaDS.AI Dresden/Leipzig”.

2021

• Full author list: Evolutionary and biomedical insights from a marmoset diploid genome assembly. Nature (2021). [link]

• Full author list: Towards complete and error-free genome assemblies of all vertebrate species. Nature 592, 737-746 (2021). [link]

• Full author list: Low threshold for cutaneous allergen sensitization bu no spontaneous dermatitis or atopy in filaggrin-deficient mice. Journal of Investigative Dermatology (2021). [link]

• Scholz, V.; Winkler, P.; Hornig, A.; Gude, M.; Filippatos, A. Structural Damage Identification of Composite Rotors Based on Fully Connected Neural Networks and Convolutional Neural Networks. Sensors 2021, 21, 2005. [link]

• Dmitrij Schlesinger, Alexander Shekhovtsov, Boris Flach: VAE Approximation Error: ELBO and Conditional Independence. (2021) [link]

• Wolfgang Dvorak, Markus Ulbricht, Stefan Woltran: "Recursion in Abstract Argumentation is Hard --- On the Complexity of Semantics Based on Weak Admissibility." In: Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.

• Markus Ulbricht, Johannes P. Wallner: Strong Explanations in Abstract Argumentation. In: Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021), February 2021.

• Rohde, F., Franke, M., Sehili, Z. et al.: Optimization of the Mainzelliste software for fast privacy-preserving record linkage. J Transl Med 19, 33 (2021). [link]

• Franke, Martin; Sehili, Ziad; Rohde, Florens; Rahm, Erhard: Evaluation of Hardening Techniques for Privacy-Preserving Record Linkage, 24th International Conference on Extending Database Technology (EDBT) 2021-03.

• Ayala, Daniel; Hernández, Irma; Ruiz, David; Rahm, Erhard: Towards the smart use of embedding and instance features for property matching, Proc. Int. Conf. on Data Engineering (ICDE), 2021-04.

• Gomez, K.; Taeschner, M.; Rostami, M. Ali; Rost, C.; Rahm, E.: Graph Sampling with Distributed In-Memory Dataflow Systems, Proc. Datenbanksysteme für Business, Technologie und Web (BTW) 2021, 2021-03.

• Rost, C.; Gomez, K.; Fritzsche, P.; Thor, A.; Rahm, E.: Exploration and Analysis of Temporal Property Graphs, 24th International Conference on Extending Database Technology (EDBT), 2021-03.

• Philippe Krajsic, Bogdan Franczyk: Variational Autoencoder for Anomaly Detection in Event Data in Online Process Mining, in Proceedings of the 23rd International Conference on Enterprise Information Systems - Volume 1: ICEIS, pages 567-574, April 2021. DOI: 10.5220/0010375905670574

• Lerm, S.; Saeedi, A.; Rahm, E.: Extended Affinity Propagation Clustering for Multi-source Entity Resolution, BTW 2021, 2021-03.

• Lin, Ying-Chi; Hoffmann, Phillip; Rahm, Erhard: Enhancing Cross-lingual Semantic Annotations Using Deep Network Sentence Embeddings. In: Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 5: HEALTHINF, pages 188-199. (Best Paper Award), 2021-02.

• Obraczka, Daniel; Schuchart, Jonathan; Rahm, Erhard: EAGER: Embedding-Assisted Entity Resolution for Knowledge Graphs, Arxiv, 2021-01.

• Rohde, Florens; Franke, Martin; Sehili, Ziad; Lablans, Martin; Rahm, Erhard: Optimization of the Mainzelliste software for fast privacy-preserving record linkage, BMC Journal of Translational Medicine, 2021-01.

• Ringo Baumann, Markus Ulbricht: "On Cycles, Attackers and Supporters --- A Contribution to The Investigation of Dynamics in Abstract Argumentation." Accpected for Publication in: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), August 2021.

    

   2020 

• Ringo Baumann, Markus Ulbricht: "On Cycles, Attackers and Supporters --- A Contribution to The Investigation of Dynamics in Abstract Argumentation." Accpected for Publication in: Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), August 2021.

• Peiwen Xiong, C. Darrin Hulsey, Carmelo Fruciano, Wai Y. Wong, Alexander Nater, Andreas F. Kautt, Oleg Simakov, Martin Pippel, Shigehiro Kuraku, Axel Meyer, Paolo Franchini: "The comparative genomic landscape of adaptive radiation in crater lake cichlid fishes" (2020). In: Molecular Ecology, Volume 30, Isse 4, pages 955-972 (Feb. 2021)
• Münster, Sander; Maiwald, Ferdinand; Lehmann, Christoph; Lazariv, Taras; Hofmann, Mathias and Niebling, Florian: An Automated Pipeline for a Browser-Based, City-Scale Mobile 4D VR Application Based on Historical Images. In Proceedings of the 2nd Workshop on Structuring and Understanding of Multimedia HeritAge Contents (2020), SUMAC'20, pages 33-40  [link]
  
  
• Franziska Kahlert, Stefan Gumhold: Partial Matching of Trajectories with Particle Orientation for Exploratory Trajectory Visualization. In Vision, Modeling, and Visualization (2020), Krüger J., Niessner M., Stückler J., (Eds.), The Eurographics Association  [link]
  
  
• Patrick Stiller, Friedrich Bethke, Maximilian Böhme, Richard Pausch, Sunna Torge, Alexander Debus, Jan Vorberger, Michael Bussmann and Nico Hoffmann: Large-Scale Neural Solvers for Partial Differential Equations. Smoky Mountains/Computational Sciences & Engineering/Conference, 2020. [link]
   
• Sunna Torge, Waldemar Hahn, René Jäkel: Transfer Learning for Domain-Specific Named Entity Recognition in German. 4th IEEE Conference on Machine Learning and Natural Language Processing in the 6th IEEE Congress on Information Science and Technology, 2020.
  
  
• Sunna Torge, Waldemar Hahn, René Jäkel, Wolfgang E. Nagel: Corpus and Baseline Model for Domain-Specific Entity Recognition in German. 4th IEEE Conference on Machine Learning and Natural Language Processing in the 6th IEEE Congress on Information Science and Technology, 2020
  
  
• Jebb, D., Huang, Z., Pippel, M. et al.: Six reference-quality genomes reveal evolution of bat adaptations. Nature 583, 578–584 (2020). [link]
  
  
• Martin Pippel, David Jebb, Franziska Patzold, Sylke Winkler, Heiko Vogel, Gene Myers, Michael Hiller, Anna K. Hundsdoerfer: A highly contiguous genome assembly of the bat hawkmoth Hyles vespertilio, GigaScience, Volume 9, Issue 1, January 2020, giaa001 [link]
  

• Wei-Fan Chen, Shahbaz Syed, Benno Stein, Matthias Hagen, and Martin Potthast. Abstractive Snippet Generation. In Yennung Huang, Irwin King, Tie-Yan Liu, and Maarten van Steen, editors, Web Conference (WWW 2020), pages 1309-1319, April 2020. ACM. [link]

• Milad Alshomary, Shahbaz Syed, Martin Potthast, and Henning Wachsmuth. Target Inference in Argument Conclusion Generation. In 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), July 2020. Association for Computational Linguistics. [link]
  
  
• Eric Peukert, Erhard Rahm, and Saeedi Alieh. Incremental Multi-source Entity Resolution for Knowledge Graph Completion. In: Harth A. et al. (eds) The Semantic Web. ESWC 2020. Lecture Notes in Computer Science, vol 12123. Springer, Cham.[link]

• Peter Christen, Dinusha Vatsalan, and Erhard Rahm. Incremental Clustering Techniques for Multi-Party Privacy-Preserving Record Linkage. In: Data & Knowledge Engineering, Volume 128, 2020. [link] 

• Ringo Baumann, Gerhard Brewka, and Markus Ulbricht. Comparing Weak Admissibility Semantics to their Dung-style Counterparts -- Reduct, Modularization, and Strong Equivalence in Abstract Argumentation. In Proceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning—Main Track. Pages 79-88. [link]

• Philippe Krajsic, Bogdan Franczyk: Lambda Architecture for Anomaly Detection in Online Process Mining using Autoencoders, 12th International Conference on Computational Collective Intelligence, 2020. [link]

• Baumann, Ringo; Heinrich, Maximilian. Timed Abstract Dialectical Frameworks: A Simple Translation-Based Approach. In: Computational Models of Argument-Proceedings of COMMA 2020, Perugia, Italy, September 4-11, 2020. [link]

• Baumann, Ringo; Heinrich, Maximilian. A Python Script for Abstract Dialectical Frameworks. Proceedings of the Third International Workshop on Systems and Algorithms for Formal Argumentation co-located with the 8th International Conference on Computational Models of Argument - COMMA 2020, September 8, 2020. [link]

• Sherif Sakr, Angela Bonifati, Hannes Voigt, Alexandru Iosup, and the computer systems and data management communities. The Future is Big Graphs! A Community View on Graph Processing Systems. CACM -, - (December 2020), 12 pages, 2020. [link]

• Shahbaz Syed, Roxanne El Baff, Khalid Al-Khatib, Johannes Kiesel, Benno Stein, and Martin Potthast. News Editorials: Towards Summarizing Long Argumentative Texts. In 28th International Conference on Computational Linguistics (COLING 2020), December 2020. Association for Computational Linguistics. [link] 

• Khalid Al-Khatib, Michael Völske, Shahbaz Syed, Nikolay Kolyada, and Benno Stein. Exploiting Personal Characteristics of Debaters for Predicting Persuasiveness. In 58th Annual Meeting of the Association for Computational Linguistics (ACL 2020), pages 7067-7072, July 2020. Association for Computational Linguistics. [link]

• Ayala, Daniel; Hernández, Irma; Ruiz, David; Rahm, Erhard: LEAPME: Learning-based Property Matching with Embeddings, Arxiv 2010.01951; 2020-10.

• Shao, Jingyu; Wang, Qing; Wijesinghe, Asiri; Rahm, Erhard: ERGAN: Generative Adversarial Networks for Entity Resolution; IEEE International Conference on Data Mining (ICDM), 2020-11.

• Franczyk, B., Hernes, M., et al: Deep learning for grape recognition. Procedia Computer Science 176, pp 1211-1220, January 2020. DOI: 10.1016/j.procs.2020.09.117.

• Augenstein, Ch., Franczyk, B.: Anomaly Detection on Data Streams – a LSTM’s Diary. In book: Research Challenges in Information Science (June 2020).  DOI: 10.1007/978-3-030-50316-1_22.

• Augenstein, Ch., Zschörnig, T., Spangenberg, N., Franczyk, B.: A generic architectural framework for Machine Learning on Data Streams. In book: Enterprise Information Systems (February 2020).  DOI: 10.1007/978-3-030-40783-4_6.

• Zeckzer, D., Hausdorf, A., Hinzmann, N., Müller, L., & Wiegreffe, D. (2020). Masakari: Visualization supported statistical analysis of genome segmentations. BMC bioinformatics, 21(1), 1-14.

• Zschörnig, T., Windolph, J., Wehlitz, R., Franczyk, B.: A Cloud-based Analytics Architecture for the Application of Online Machine Learning Algorithms on Data Streams in Consumer-centric Internet of Things Domains. In: Proceedings of the 5th International Conference on Internet of Things, Big Data and Security - Volume 1: IoTBDS, 189-196, 2020. (ISBN: 978-989-758-426-8)

• Maktabi M., Köhler H., Ivanova M., Neumuth T., Rayes N., Seidemann L., et al.: Classification of Hyperspectral Endocrine Tissue Images Using Support Vector Machines. Int J Med Robot. 2020 May 10;2121.

• Gockel I., Jansen-Winkeln B., Sucher R., Rayes N., Thieme R., Moulla Y., et al.: Hyperspektral-Imaging (HSI) – eine verlässliche Gewebedifferenzierung? Zentralbl Chir [Internet]. 2020;145(02):125–9. [Link]

• Gaebel J, Wu H-G, Oeser A, Cypko MA, Stoehr M, Dietz A, et al. Modeling and Processing Up-To-Dateness of Patient Information in Probabilistic Therapy Decision Support. Artificial Intelligence in Medicine [Internet]. 2020;101842. [Link]

• Christian Kaltenecker, Alexander Grebhahn, Norbert Siegmund, Sven Apel: The Interplay of Sampling and Machine Learning for Software Performance Prediction. IEEE Software, 2020.

  2019

• Jan Frenzel, René Jäkel: Job Performance Overview of Apache Flink and Apache Spark Applications, Research Poster at The International Conference for High Performance Computing, Networking, Storage, and Analysis (SC19), 2019 [link] 

• Siavash Ghiasvand, Florina M. Ciorba: Anomaly Detection in High Performance Computers: A Vicinity Perspective, ISPDC 2019, doi.org/10.1109/ISPDC.2019.00024

• Siavash Ghiasvand: uPAD: Unsupervised Privacy-Aware Anomaly Detection in High Performance Computing Systems, ICPRAM 2019, doi.org/10.5220/0007582208520859

• Maiwald, Ferdinand; Bruschke, Jonas; Lehmann, Christoph and Niebling, Florian. A 4D information system for the exploration of multitemporal images and maps using photogrammetry, web technologies and VR/AR. Virtual Archaeology Review, 10(21), 1-13, 2019.

• Elvis Koci, Dana Kuban, Nico Luettig, Dominik Olwig, Maik Thiele, Julius Gonsior, Wolfgang Lehner, Oscar Romero: XLIndy: Interactive Recognition and Information Extraction in Spreadsheets. DocEng 2019: 25:1-25:4

• Elvis Koci, Maik Thiele, Josephine Rehak, Oscar Romero, and Wolfgang Lehner. "Deco: A dataset of annotated spreadsheets for layout and table recognition". In the 15th IAPR International Conference on Document Analysis and Recognition (ICDAR'19). (In Press)

• Elvis Koci, Dana Kuban, Nico Luettig, Dominik Olwig, Maik Thiele, Julius Gonsior, Oscar Romero, and Wolfgang Lehner. "Xlindy: Interactive recognition and information extraction in spreadsheets". In ACM Symposium on Document Engineering (DocEng ’19). [link]

• Taras Lazariv, Christoph Lehmann. Goodness-of-Fit Tests for Large Data Sets. Symposium on Data Science and Statistics, Bellevue, Washington, May/June, 2019.

• Gärtner, F.; Stadler, P.F. Direct Superbubble Detection. Algorithms 2019, 12, 81.[link]

• Obraczka, D.; Saeedi, A.; Rahm, E.: Knowledge Graph Completion with FAMER , Proc. KDD workshop on Data Integration to Knowledge Graphs (DI2KG) [link]
  

• M. Ali Rostami, Eric Peukert, Moritz Wilke, Erhard Rahm: Big graph analysis by visually created workflows. BTW 2019

• M. Ali Rostami, Matthias Kricke, Eric Peukert, Stefan Kühne, Moritz Wilke, Steffen Dienst, Erhard Rahm: BIGGR: Bringing Gradoop to Applications. Datenbank-Spektrum 19(1): 51-60; 2019 [link]

• Gerhard Heyer, Jochen Tiepmar: A Big Data Case Study in Digital Humanities: Creating a Performance Benchmark for Canonical Text Services. Datenbank-Spektrum pp 1–9; 2019. [Springer]

• Martin Franke, Marcel Gladbach, Ziad Sehili, Florens Rohde, Erhard Rahm. ScaDS Research on Scalable Privacy-preserving Record Linkage, Datenbank-Spektrum; 2019

• Martin Hahmann, Claudio Hartmann, Lars Kegel, Wolfgang Lehner: Large-Scale Time Series Analytics, Novel Approaches for Generation and Prediction, Datenbank-Spektrum; 2019

• Erhard Rahm, Wolfgang E. Nagel, Eric Peukert, René Jäkel, Fabian Gärtner, Peter F. Stadler, Daniel Wiegreffe, Dirk Zeckzer, Wolfgang Lehner:  Big Data Competence Center ScaDS Dresden/Leipzig: Overview and selected research activities,  Datenbank-Spektrum; 2019

• Frey, J.; Hofer, M.; Obraczka, D.; Lehmann, J.; Hellmann, S.: DBpedia FlexiFusion The Best of Wikipedia>Wikidata>Your Data, ISWC 2019

• Christen, Victor; Christen, Peter; Rahm, Erhard, Informativeness-Based Active Learning for Entity Resolution, accepted for Proc. International Workshop on Data Integration and Applications(DINA@ECML-PKDD), Würzburg 2019

• Rost, C.; Thor, A.; Fritzsche, P.; Gomez, K.; Rahm, E.: Evolution Analysis of Large Graphs with Gradoop, Proc. of Intl. Workshop on Advances in managing and mining large evolving graphs (LEG@ECML-PKDD) 2019

• Franke, M.; Sehili, Z.; Rahm, E.:PRIMAT: A Toolbox for Fast Privacy-preserving Matching, PVLDB 12(12): 1826-1829, 2019

• Obraczka, D.; Saeedi, A.; Rahm, E.: Knowledge Graph Completion with FAMER: Proc. KDD workshop on Data Integration to Knowledge Graphs (DI2KG), 2019

• Kricke, M.; Peukert, E.; Rahm, E.: Graph data transformations in GRADOOP, Proc. BTW, March 2019

• Rahm, E,; Härder, T.: Editorial, Datenbankspektrum 19(1), 2019

• Rost, Christopher; Thor, Andreas; Rahm, Erhard: Temporal Graph Analysis using Gradoop, Proc. BTW workshops, LNI, 2019

• Obraczka, Daniel; Ngonga Ngomo, Axel-Cyrille, Dragon: Decision Tree Learning for Link Discovery, Web Engineering, 2019

• Shahbaz Syed, Michael Völske, Nedim Lipka, Benno Stein, Hinrich Schütze, and Martin Potthast. Towards Summarization for Social Media - Results of the TL;DR Challenge. In 12th International Natural Language Generation Conference (INLG 2019), November 2019. [pdf]

• Ulbricht, Markus. Understanding Inconsistency: A Contribution to the Field of Non-monotonic Reasoning. Leipzig, 2019. [link]

• Röhling, Martin Max; Grimmer, Martin; Kreusel, Dennis; Hoffmann, Jörn; Franczyk, Bogdan. Standardized container virtualization approach for collecting host intrusion detection data.  Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 18, pages 459–463 (2019). [link]

• Grimmer, Martin; Röhling, Martin Max; Kreusel, Dennis; Ganz, Simon. A Modern and Sophisticated Host Based Intrusion Detection Data Set. Proceedings of 16. Deutscher IT-Sicherheitskongress, 2019 (Hrsg.): IT-Sicherheit als Voraussetzung für eine erfolgreiche Digitalisierung, S. 135-145, 16. Deutscher IT-Sicherheitskongress, 2019 SecuMedia, 2019. [link]

• Kühne, S.; Scheller, F.; Kondziella, H.; Reichelt, D. G.; Bruckner, T. Decision Support System for Municipal Energy Utilities: Approach, Architecture, and Implementation. In: Chemical Engineering & Technology. 2019. 42 (9). S. 1914-1922. [link]

• Reichelt, D. G.; Kühne, S.; Hasselbring, W. On the Validity of Performance Antipatterns at Code Level. In: Softwaretechnik-Trends 39. 2019. S. 32-34. [link]

• Reichelt, D. G.; Kühne, S.; Hasselbring, W. PeASS: A Tool for Identifying Performance Changes at Code Level 2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE). IEEE. 2019. S. 1146-1149. [link]

• Spangenberg, N., Augenstein, C., Wilke, M., Franczyk, B.: An intelligent and data-driven decision support solution for the Online Surgery Scheduling problem. In: Hammoudi S., Smialek M., Camp O., Filipe J. (Hrsg.). Lecture Notes in Business Information Processing (LNBIP, volume 363). S.82-103, 2019. DOI: 10.1007/978-3-030-26169-6_5.

• Nsonga, B., Niemann, M., Fröhlich, J., Staib, J., Gumhold, S., & Scheuermann, G. (2019). Detection and visualization of splat and antisplat events in turbulent flows. IEEE transactions on visualization and computer graphics, 26(11), 3147-3162.

• Nsonga, B., Scheuermann, G., Gumhold, S., Ventosa-Molina, J., Koschichow, D., & Fröhlich, J. (2019). Analysis of the near-wall flow in a turbine cascade by splat visualization. IEEE transactions on visualization and computer graphics, 26(1), 719-728.

  2018

• Gocht, Andreas; Lehmann, Christoph; Schöne, Robert. A New Approach for Automated Feature Selection. In: 2018 IEEE International Conference on Big Data (Big Data). IEEE, 2018. S. 4915-4920.

• Jochen Tiepmar (2018). Big Data and Digital Humanities. Archives of Data Science, Series A. [KITopen]

•  Elvis Koci, Maik Thiele, Wolfgang Lehner, Oscar Romero: Table Recognition in Spreadsheets via a Graph Representation. DAS 2018: 139-144

• Reichelt, D.G.; Meyer, L.-P.; Kühne, S.: Better a Microbenchmark on a Cluster than a User at the Office - Flink Cluster Benchmarking. SSP Proceedings 2018. In publication, preprint published [Link]

• Tanmoy Bhattacharya; Nancy Retzlaff; Damián E Blasi; William Croft; Michael Cysouw; Daniel Hruschka; Ian Maddieson; Lydia Müller; Eric Smith; Peter F Stadler; George Starostin; Hyejin Youn: Studying language evolution in the age of big data. Journal of Language Evolution, Volume 3, Issue 2, 1 July 2018, Pages 94–129 [Link]

• Maria Waldl; Bernhard C. Thiel; Roman Ochsenreiter; Alexander Holzenleiter; João Victor de Araujo Oliveira; Maria Emília M. T. Walter; Michael T. Wolfinger;Peter F. Stadler: TERribly Difficult: Searching for Telomerase RNAs in Saccharomycetes. Genes 2018, 9(8), 372 [Link]

• Kai Kamm; Hans-Jürgen Osigus; Peter F. Stadler; Rob DeSalle; Bernd Schierwater: Trichoplax genomes reveal profound admixture and suggest stable wild populations without bisexual reproduction. Scientific Reportsvolume 8, Article number: 11168 (2018) [Link]

• Prohaska SJ.; Berkemer SJ.; Gärtner F.; Gatter T.; Retzlaff N.; Students of the Graphs and Biological Networks Lab 2017; Höner Zu Siederdissen C.; Stadler PF.: Expansion of gene clusters, circular orders, and the shortest Hamiltonian path problem. J Math Biol. 2018 Aug;77(2):313-341 [Link]

• Jakob L. Andersen; Rolf Fagerberg; Christoph Flamm; Rojin Kianian; Daniel Merkle; Peter F. Stadler: Towards Mechanistic Prediction of Mass Spectra Using Graph Transformation. MATCH Commun. Math. Comput. Chem. 80 (2018) 705-731 [Link]

• Hoffmann A.; Fallmann J.; Vilardo E.; Mörl M.; Stadler PF.; Amman F.: Accurate mapping of tRNA reads. Bioinformatics. 2018 Apr 1;34(7):1116-1124 [Link]

• A. D. Lokits; H. Indrischek; J. Meiler; H. E. Hamm; P. F. Stadler: Tracing the evolution of the heterotrimeric G protein α subunit in Metazoa. BMC Evolutionary Biology 2018 Apr;18(1):51 [Link]

• Canzler S.; Stadler PF.; Schor J.: The fungal snoRNAome. RNA. 2018 Mar;24(3):342-360 [Link]

• Susanne N. Gröbner; Barbara C. Worst et al.: The landscape of genomic alterations across childhood cancers. Nature, 555:321–327, 2018. Nature [Link]

• Gärtner, Fabian and Siederdissen, Christian and Müller, Lydia and Stadler, Peter F.: Coordinate systems for supergenomes. Algorithms for Molecular Biology 13 (1): 15 [Link]

• Dienst, S.; Kipp, A.; Kötter, T.; Kühne, S.: Analyse großer Graph-Daten mit Gradoop und KNIME. Bitkom Big-Data.AI Summit 2018 – Data-driven Business Innovations for the Digital World. 2018

• Frenzel, J.; Feldhoff, K.; Jäkel, R.; Müller-Pfefferkorn, R.: Tracing of Multi-Threaded Java Applications in Score-P Using Bytecode Instrumentation. ARCS 2018: 31st GI/ITG International Conference on Architecture of Computing Systems - Workshop Proceedings, April, 2018 [Link]

• Frenzel, J.; Sastri, Y.; Lehmann, C.; Lazariv, T.; Jäkel, R.; Nagel, W. E.: A Generalized Service Infrastructure for Data Analytics. 4th IEEE International Conference on Big Data Computing Service and Applications [Link]

• Memon, A. B.; Meyer, K.; Thieme, M.; Meyer, L.-P.: Inter-InnoLab collaboration. An investigation of the diversity and interconnection among Innovation Laboratories. Journal of Engineering and Technology Management 47. 2018

• Meyer, L.-P.; Frenzel, J.; Peukert, E.; Jäkel, R.; Kühne, S.: Big Data Services - Erfahrungen im Big-Data-Kompetenzzentrum. In Meyer K., Klingner S., Zinke C. (eds) Service Engineering. Springer Vieweg, Wiesbaden. [Link]

• Reichelt, David Georg, and Stefan Kühne. "Better Early Than Never: Performance Test Acceleration by Regression Test Selection." Companion of the 2018 ACM/SPEC International Conference on Performance Engineering. ACM, 2018. [Link]

• Reichelt, David Georg, and Stefan Kühne. "How to Detect Performance Changes in Software History: Performance Analysis of Software System Versions." Companion of the 2018 ACM/SPEC International Conference on Performance Engineering. ACM, 2018. [Link]

• Spangenberg, Norman and Augenstein, Christoph and Franczyk, Bogdan and Wilke, Moritz. Implementation of a Situation Aware and Real-Time Approach for Decision Support in Online Surgery Scheduling. CBMS 2018.
  
  
• Spangenberg, Norman and Wilke, Moritz and Augenstein, Christoph and Franczyk, Bogdan. Online Surgery Rescheduling - A Data-driven Approach for Real-time Decision Support. ICEIS 2018.

• Tiepmar, J.: Implementation and Evaluation of the Canonical Text Service Protocol as Part of a Research Infrastructure in the Digital Humanities. PhD Thesis, Leipzig University. 2018 [Qucosa]

• Zeckzer D., Wiegreffe, D., Müller, L.: Analyzing Histone Modifications Using Tiled Binned Clustering and 3D Scatter Plots. In 26th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2018
   
• Wiegreffe, D., Müller, L., Steuck, J., Zeckzer, D.,  Stadler, P. F.: The Sierra Platinum Service for generating peak-calls for replicated ChIP-seq experiments. BMC research notes, 11(1), 512.
  
• Wiegreffe, D., Alexander, D., Stadler, P.F.,  Zeckzer, D.: RNApuzzler: Efficient Outerplanar Drawing of RNA-Secondary Structures. Bioinformatics, pp. bty817.

• Grimmer, Martin; Röhling, Martin Max; Kricke, Matthias; Franczyk, Bogdan; Rahm, Erhard. Intrusion Detection on System Call Graphs Proceedings of DFN-CERT, DFN-Konferenz "Sicherheit Systemen" 25 (Hrsg.): Sicherheit in vernetzten Systemen, S. G1-G18, DFN-CERT Services GmbH, 2018. [link]

• 2017

• Elvis Koci, Maik Thiele, Oscar Romero, Wolfgang Lehner: Table Identification and Reconstruction in Spreadsheets. CAiSE 2017: 527-541

• Ahmadov, A.;  Thiele, M; Lehner, W; and Wrembel, R.: Context Similarity for Retrieval-Based Imputation. Appears In International Symposium on Foundations and Applications of Big Data Analytics, Sydney, Australia, August 1-3, 2017

• Alexandre Paschoal, Irma Lozada-Chavez, Douglas Domingues: ceRNAs in plants: computational approaches and associated challenges for target mimics research. Briefings in Bioinformatics 2017

• Ali Yazbeck, Kifah R Tout, Peter F Stadler, Jana Hertel: Towards a Consistent, Quantitative Evaluation of MicroRNA Evolution. J. Integrative Bioinformatics 2017

• Amann, W: Vergleich und Evaluation von RDF-on-Hadoop-Lösungen. Workshop Proceedings Datenbanksysteme für Business, Technologie und Web (BTW) 2017 Lecture Notes in Informatics(LNI), GI 2017 [PDF]

• Bärbel M.R. Stadler, Peter F. Stadler: Oriented Components and their Separations. Applied General Topology, in press 2017

• Christen, V.; Groß, A.; Fisher, J.y; Wang, Q.; Christen, P.; Rahm, E.: Temporal group linkage and evolution analysis for census data. Proc. 19th Int. Conf. on Extending Database Technology (EDBT), Venice, 2017

• Fritzsch, C.; Hoffmann, J.; Bogdan, M.: Separated Random Number Generators for Virtual Machines. To appear in: Proc. 47. Jahrestagung der Gesellschaft für Informatik e.V. (GI), 2017

• Gerighausen, D.; Hausdorf, A.; Zänker, S.; Zeckzer, D.: iDotter – an interactive dot plot viewer, WSCG 2017 

• D. Gerighausen, L. Müller, J. Steuck, D. Zeckzer, P. F. Stadler.  The Sierra Platinum Service for Generating Peak-Calls for Replicated ChIP-Seq Experiments. BMC Research Notes (under review)

• Jan Frenzel, Kim Feldhoff, René Jäkel, Ralph Müller-Pfefferkorn Tracing of Multi-Threaded Java Applications in Score-P Using JVMTI and User Instrumentation (noch unveröffentlicht, akzeptiert bei PARS 17)

• Gralka, P.; Grottel, S.; Staib, J.; Schatz, K.; Karch, G.; Hirschler, M.; Krone, M.; Reina, G.; Gumhold, S.; Ertl, T.: 2016 IEEE Scientific Visualization Contest Winner – Visual and Structural Analysis of Point-based Simulation Ensembles, IEEE CG&A 2017 (to appear)

• Grallert, T.; Tiepmar, J.; Eckart, T.; Goldhahn, D.; Kuras, C. (2017). Digital Muqtabas CTS Integration in CLARIN. In CLARIN Annual Conference 2017

• Grottel, S.; Müller, C.; Staib, T.; Gumhold, S. (2017): Extraction and Visualization of Structure-Changing Events in Molecular Dynamics Data in Proceedings of TopoInVis Workshop 2017, p. to appear.

• Hecht, R.; Kalla, M.; Krüger, T. (2017) Crowd-sourced data collection to support automatic classification of building footprint data. In: Proceedings of the 28th International Cartographic Conference (ICC2017), July 1-8th, 2017, Washington DC, USA.

• Hirmer, P.; Waizenegger, T.; Falazi, G.; Abdo, M.; Volga, Y.; Askinadze, A; Liebeck, M.; Conrad, S.; Hildebrandt, T.; Indiono, C.; Rinderle-Ma, S.; Grimmer, M.; Kricke, M.; Peukert, E.: The First Data Science Challenge at BTW 2017. Datenbank-Spektrum, 17.2 (2017) (invited)

• Junghanns, M; Petermann, A.; Neumann, M.; Rahm, E.: Management and Analysis of Big Graph Data: Current Systems and Open Challenges. In: Big Data Handbook (eds.: S. Sakr, A. Zomaya) , Springer 2017, [PDF]

• Junghanns, M.; Petermann, A.; Rahm, E.; Distributed Grouping of Property Graphs with GRADOOP, Proc. Datenbanksysteme für Business, Technologie und Web (BTW) 2017, 2017-03, GI 2017[PDF]

• Junghanns, M.; Petermann, A.; Teichmann, N.; Rahm, E.: The Big Picture: Understanding large-scale graphs using Graph Grouping with GRADOOP. Proc. Datenbanksysteme für Business, Technologie und Web (BTW) 2017 (Demo paper), 2017-03 [PDF]

• Junghanns, M.; Kießling, M.; Averbuch, A., Petermann, A.; Rahm, E.: Cypher-based Graph Pattern Matching in Gradoop. ACM SIGMOD workshop on Graph Data Management Experiences and Systems (GRADES), 2017-05 [PDF]

• Kemper, S.; Petermann, A.; Junghanns, M.: Distributed FoodBroker: Skalierbare Generierung graphbasierter Geschäftsprozessdaten. In BTW (Workshops) (pp. 105-110), GI 2017 [PDF]

• Kegel, L.; Hahmann, M; and Lehner, W.: Generating What-If Scenarios for Time Series Data. In Proceedings of the 29th International Conference on Scientific and Statistical Database Management (SSDBM '17), New York, NY, USA, 2017

• Kister, U.; Klamka, K.; Tominski, C.; Dachselt, R.; GraSp: Combining Spatially-aware Mobile Devices and a Display Wall for Graph Visualization and Interaction. Computer Graphics Forum (Proceedings of Eurographics/IEEE EuroVis 2017). 2017.

• Kricke, M., Martin Grimmer, Martin Junghanns, Eric Peukert, Erhard Rahm: Data-Science-Challenge: Graph-based analysis and demand prediction for bike rentals, BTW 2017, accepted

• Kricke, M.; Grimmer, M.; Schmeißer, M.: Preserving Recomputability of Results from Big Data Transformation Workflows. Workshop Proceedings Datenbanksysteme für Business, Technologie und Web (BTW) 2017 Lecture Notes in Informatics(LNI), GI 2017 [PDF]

• Kricke, Matthias; Grimmer, Martin; Schmeißer, Michael: Preserving Recomputability of Results from Big Data Transformation Workflows Depending on External Systems and Human Interactions, Datenbank-Spektrum, 17.2 (2017) (invited)

• Nardini, P.; Böttinger, M.; Scheuermann, G.; Schmidt, M.: Visual Study of the Benguela Upwelling System using Pathline Predicates, Visualization in Environmental Sciences 2017

• Nentwig, Markus; Groß, Anika; Möller, Maximilian; Rahm, Erhard: Distributed Holistic Clustering on Linked Data. Proc. OTM 2017 - Confederated International Conferences: CoopIS, C&TC, and ODBASE 2017, LNCS 10574, pp 371-382

• Paschoal, Alexandre; Lozada-Chavez, Irma; Domingues, Douglas: ceRNAs in plants: computational approaches and associated challenges for target mimics research. Briefings in Bioinformatics 2017, doi: 10.1093/bib/bbx058.

• Petermann, A.; Micale G.; Bergami G.; Junghanns, M.; Pulvirenti, A.; Rahm, E.: Mining and Ranking of Generalized Multi-Dimensional Frequent Subgraphs. Proc. Int.Conf. on Digital Information Management (ICDIM) 2017

• Petermann, A.: Graph Pattern Mining for Business Decision Support, VLDB PhD Workshop 2017, 2017-08

• Petermann, A.; Micale, G.; Bergami, G.; Pulvirenti, A.; Rahm, E.:  Mining and Ranking of Generalized Multi-Dimensional Frequent Subgraphs. Proc. International Conference on Digital Information Management (ICDIM) 2017

• Petermann, A.; Junghanns, M.; Rahm, E.;  DIMSpan - Transactional Frequent Subgraph Mining with Distributed In-Memory Dataflow Systems. Proc. International Conference on Big Data Computing, Applications and Technologies (BDCAT) 2017 [PDF]

• Pretzsch, F.: Duplikaterkennung in der Graph-Processing-Platform GRADOOP. Workshop Proceedings Datenbanksysteme für Business, Technologie und Web (BTW) 2017 Lecture Notes in Informatics(LNI), GI 2017 [PDF]

• Raith, F.; Röber, N.; Haak, H.; Scheuermann, G.:Visual Eddy Analysis of the Agulhas Current, Visualization in Environmental Sciences 2017

• Saeedi, Alieh; Peukert, Eric; Rahm, Erhard: Comparative Evaluation of Distributed Clustering Schemes for Multi-source Entity Resolution, Proc. ADBIS, LNCS, 2017-09 [PDF]

• Sastri, Y.; Feldhoff, K.; Starruß, J.; Jäkel, R.; and Müller-Pfefferkorn, R.; "A Workflow for the Integral Performance Analysis of Cloud Applications Using Monitoring and Tracing Techniques", ICCBDC 2017, to appear

• Schlesinger, D.; Jug, F.; Myers, G.; Rother, C.; Kainmüller, D.; “Crowd Sourcing Image Segmentation with iaSTAPLE”, ISBI 2017. [pdf]

• Spangenberg, N.; Augenstein, C.; Franczyk, B.; Wagner, M.; Apitz, M.; Kenngott, H.: Method for intrasurgical phase detection by using real-time medical device data, In: Proceedings of International Conference on Computer-based Medical Systems 2017

• Spangenberg, N.; Roth, M.; Mutke, S.; Franczyk, B.: Big Data in der Logistik - Ein ganzheitlicher Ansatz für die datengetriebene Logistikplanung, -überwachung und -steuerung. Industrie 4.0 Management 33 (2017)

• Spangenberg, N.; Wilke, M.; Franczyk, B.: A Big Data architecture for intra-surgical remaining time predictions. Proceedings of the International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH) 2017

• Stadler, Bärbel M.R.; Stadler, Peter F.: Oriented Components and their Separations. Applied General Topology, in press 2017

• Staib, J.; Grottel, S.; Gumhold, S.: Temporal Focus+Context for Clusters in Particle Data, Presentation at VMV Sep. 2017

• Swoboda, O.: Serverseitige Aggregation von Zeitreihendaten in verteilten NoSQL-Datenbanken. In BTW (Workshops) (pp. 365-373), GI 2017 [PDF]

• Tiepmar, J., G. Heyer, G.: An humanistsic overview of Canonical Text Services. To appear in: International Journal of Language and Linguistics 2017

• Tiepmar, J.; Heyer, G. (2017). An Overview of Canonical Text Services. Linguistics and Literature Studies Vol. 5(2) , 132 - 148 . doi: 10.13189/lls.2017.050209 [JOURNAL]

• Tiepmar, J.; Eckart, T.; Goldhahn, D.; Kuras, C. (2017). Integrating Canonical Text Services into CLARIN's Search Infrastructure. In Linguistics and Literature Studies, 5 , 99 - 104. doi: 10.13189/lls.2017.050205 [JOURNAL]

• Torge, S.; Jäkel, R.; Winkler, P.; Schlesinger, D. and Frenzel, J.;(2017) Deep Learning and High Performance Computing, in: Fourth Edinburgh Deep Learning Workshop, 2017

• Vatsalan, D.; Sehili, Z.; Christen, P.; Rahm, E.: Privacy-Preserving Record Linkage for Big Data: Current Approaches and Research Challenges. In: Big Data Handbook (eds.: S. Sakr, A. Zomaya) ,Springer 2017, [PDF]

• Volke, S.; Zeckzer D.; Middendorf M.; Scheuermann, G.: Visualizing Topological Properties of the Search Landscape of Combinatorial Optimization Problems, Topological Methods in Data Analysis and Visualization IV: Theory, Algorithms, and Applications, 04/2017, p.69-85, Springer, 2017.

• von Zadow, U.; Dachselt, R.; GIAnT: Visualizing Group Interaction at Large Wall Displays. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. CHI '17, Denver, CO, USA. ACM, 2639-2647, 2017.

• 2016

• Bach, B.; Carpendale, S.; Collins, C.; Dachselt, R.; Dwyer, T.; Lee, B.; Immersive Analytics: Exploring Future Interaction and Visualization Technologies for Data Analytics. In Companion Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces. ISS '16, Niagara Falls, ON, Canada. ACM, 2016.

• Becker, C.; Tiepmar, J.; Heyer, G.: Case study: Preparing a TEI corpus for Canonical Text Services, In Anwendungen Linguistische Informatik - Seminar, Leipzig, 2016 [PDF]

• Berto, S.; Perdomo-Sabogal, A.; Gerighausen, D.; Qin, J.; Nowick, K: A consensus network of gene regulatory factors in the human frontal lobe, Frontiers in Genetics, (2016)

• Braunschweig, K.; Thiele, M.; Koci, E.; Lehner, W.: Putting Web Tables into Context. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (KDIR), Porto, Portugal, November 9-11, 2016

• Cheema, M. F.; Jänicke, S.; Blumenstein,  J.; Scheuermann, G.: A Directed Concept Search Environment to Visually Explore Texts Related to User-defined Concept Models. Proceedings of the 7th International Conference on Information Visualization Theory and Applications, IVAPP 2016.

• David C Krakauer, Lydia Müller, Sonja J. Prohaska, Peter F. Stadler: Design Specifications for Cellular Regulation. Th Biosci 135: 231-240 (2016)

• Dienst, S.; Beseler, J.: Automatic Anomaly Detection in Offshore Wind SCADA Data. In: Proceedings of WindEurope Summit 2016 [PDF]

• M. Ehrhardt, R. Höhne, J. Staib (2016). In Leichtbaustrukturen zoomen | kunststoffe.de. https://www.kunststoffe.de/produkte/uebersicht/beitrag/in-leichtbaustrukturen-zoomen-plattformunabhaengige-visualisierungssoftware-vom-ilk-2425897.html. Accessed: 2017-6-23.

• Grottel, S.; Reina, G.; Krone, M.; Müller, C. and Ertl,T.; (2016). „MegaMol™ - for Fun and Profit“ in Workshop on Visualization in Practice.

• Grottel, P. Gralka, J. Staib, K. Schatz, G. K. Karch, M. Hirschler, M. Krone, G. Reina, S. Gumhold and T. Ertl (2016), Visual and Structural Analysis of Point-based Simulation Ensembles (IEEE VIS, Scientific Visualization Contest, Winning Entry).

• Grunzke, R.; Jug, F.; Schuller, B.; Jäkel, R.; Myers, G.; Nagel, W. E.: Seamless HPC Integration of Data-intensive KNIME Workflows via UNICORE, 4th International Workshop on Parallelism in Bioinformatics (PBio 2016), accepted

• Grunzke, R.; Krüger, J.; Jäkel, R.; Nagel, W. E.; Herres-Pawlis, S.; Hoffmann, A.: Metadata Management in the MoSGrid Science Gateway - Evaluation and the Expansion of Quantum Chemistry Support, Journal of Grid Computing, 2016, 1-13

• Grunzke, R.; Hartmann, V.; Jejkal, T.; Herres-Pawlis, S.; Hoffmann, A.; Deicke, A.; Schrade, T.; Stotzka, R.; Nagel, W. E.: Towards a Metadata-driven Multi-community Research Data Management Service, 2016 8th International Workshop on Science Gateways (IWSG), accepted

• Hahmann, M.; Hartmann, C.; Kegel, L.; Habich, D.; Lehner, W.: Big by blocks: modular analytics. In it - Information Technology, Vol. 58, Issue 4, 2016

• Herold, H.; Hecht, R.; Meinel, G. (2016) Old maps for land use change monitoring - analysing historical maps for long-term land use change monitoring. In: van Dijk, T. C.; Schommer, C. (Hrsg.) Proceedings of the International Workshop Exploring Old Maps (EOM 2016), University of Luxembourg, Esch-sur-Alzette, Luxembourg, 11–12.

• Hoffmann, J.; Zeckzer, D.; Bogdan, M.: „Using FPGAs to Accelerate Myers Bit-Vector Algorith“, XIV Mediterranian Conference on Medical and Biological Engineering and Computing 2016, pp 529 -535, IFMBE Proceedings, Springer, Heidelberg 2016

• Hahmann, M.; Hartmann, C.; Kegel, L.; Habich, D.; Lehner, W.: Big by blocks: modular analytics. In it - Information Technology, Vol. 58, Issue 4, 2016

• Höhne, R.; Staib, J.; Multi-scale visualisation - key to an enhanced understanding of materials. Carbon Composites Magazin. 4/2016. ISSN 2366-8024

• Jäkel, R.; Müller-Pfefferkorn, R.; Kluge, M.; Grunzke, R.; Nagel W.E.: Architectural Implications for Exascale based on Big Data Workflow Requirements, book on "Big Data & HPC“ (accepted)

• Junghanns, M.; Petermann, A.; Teichmann, N.; Gomez, K.; Rahm, E.: Analyzing Extended Property Graphs with Apache Flink. Proc. Int. SIGMOD workshop on Network Data Analytics (NDA). 2016-07, [PDF]

• Kegel, L.; Hahmann, M.; Lehner, W.: Template-based Time Series Generation with Loom. In 19th International Conference on Extending Database Technology (EDBT/ICDT Workshops), Bordeaux, France, March 15-18, 2016

• Kirillov, A.; Schlesinger, D.; Zheng, S.; Savchynskyy, B.; Torr, P.H.S.; Rother, C.: Joint Training of Generic CNN-CRF Models with Stochastic Optimization, ACCV 2016, in press. [PDF]

• Kirillov, A.; Shekhovtsov, A.;Rother, C. ; Savchynskyy,  B.; “Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization”, NIPS 2016, in press. [preprint]

• Kister, U.; Reipschläger, P.; Dachselt, R.; MultiLens: Fluent Interaction with Multi-Functional Multi-Touch Lenses for Information Visualization. In Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces. ISS '16, Niagara Falls, ON, Canada. ACM, 139-148, 2016.

• Krakauer, David C ; Müller, Lydia; Prohaska, Sonja J.; Stadler, Peter F.: Design Specifications for Cellular Regulation. Theory Bioscience 135: 231-240

• Langner, R.; von Zadow, U.; Horak, T.; Mitschick, A.; Dachselt, R.; Content Sharing Between Spatially-Aware Mobile Phones and Large Vertical Displays Supporting Collaborative Work. In Collaboration Meets Interactive Spaces. Springer International Publishing, 75-96, 2016.

• Müller, L; Gerighausen, D.; Farman, M.; Zeckzer, D.: Sierra platinum: a fast and robust peak-caller for replicated ChIP-seq experiments with visual quality-control and -steering, BMC Bioinformatics, 09/2016, Volume 17, Issue 1, p.1--13, (2016)

• Mustikovela, S.K.; Yang, M. Y.; Rother,C.; “Can Ground Truth Label Propagation from Video help Semantic Segmentation?”, Video Segmentation Workshop, ECCV 2016. [PDF]

• Nentwig, M., A. Groß, E. Rahm: Holistic Entity Clustering for Linked Data. Proc. IEEE International Conference on Data Mining Workshop, ICDMW, 2016

• Nentwig, M. A. Groß, E. Rahm: A Clustering Approach for Holistic Link Discovery (Project overview). Proc. LWDA 2016

• Nentwig, M.. Hartung, A. Ngonga Ngomo, E. Rahm: A Survey of Current Link Discovery Frameworks. Semantic Web Journal, 2016

• Petermann,A.  M. Junghanns, S. Kemper, K. Gomez, N. Teichmann, E. Rahm: Graph Mining for Complex Data Analytics. Proc. ICDM 2016 (Demo paper)

• Petermann, A.; Junghanns, M.: Scalable Business Intelligence with Graph Collections. it - Information Technology Special Issue: Big Data Analytics. 2016-08

• Perera, K. S.; Hahmann, M.; Lehner, W.; Pedersen, T. B.; Thomsen, C.: Efficient Approximate OLAP Querying Over Time Series. In 20th International Database Engineering & Applications Symposium (IDEAS ‘16), Montreal, Canada, July 11-13, 2016

• Pogrzeba, H. D.; Tiepmar, J.; Heyer, G.: Visualisierungen für CTS Text Miner, In Anwendungen Linguistische Informatik - Seminar, Leipzig, 2016 [PDF]

• Rahm, E.: Big Data Analytics (Editorial), it - Information Technology Special Issue: Big Data Analytics 2016-08

• Rahm, E.: The Case for Holistic Data Integration. Proc. ADBIS Conf.,Aug. 2016 (invited contribution)

• Reckziegel, M.; Jänicke, S.; Scheuermann,  G.: CTRaCE: Canonical Text Reader and Citation Exporter. In Digital Humanities 2016: Conference Abstracts. Jagiellonian University & Pedagogical University, Kraków, pp. 869-871, 2016.

• Richmond, D. L.; Kainmueller, D.; Yang, M. Y.; Myers, E. W. ; Rother, C.: Mapping Auto-context Decision Forests to Deep ConvNets for Semantic Segmentation, BMVC 2016. [PDF]

• Sauer, A. (2016) Aufbereitung, Auswertung und Visualisierung der Ergebnisse von Wasserhaushaltssimulationen für Sachsen mit ArcEGMO auf Basis von 10 alternativen Klimaprojektionen. In: Thinh, N.X. (Hrsg.) Modeling and Simulation of Ecosystems. Rhombos-Verlag, Berlin, 21–35.

• Schemala, D., Schlesinger, D., Winkler, P., Herold, H. and Meinel, G. (2016) Semantic segmentation of settlement patterns in gray-scale map images using RF and CRF within an HPC environment, in: GEOBIA 2016 conference proceedings, 14-16 September 2016.

• Sehili, Z.; Rahm, E.: Speeding up Privacy Preserving Record Linkage for Metric Space Similarity Measures. Datenbank-Spektrum. Pages 1-10, 2016, [PDF]

• Sollich, H.; von Zadow, U.; Pietzsch, T.; Tomancak, P.; Dachselt, R.; Exploring Time-dependent Scientific Data Using Spatially Aware Mobiles and Large Displays. In Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces. ISS '16, Niagara Falls, ON, Canada. ACM, 349-354, 2016.

• Spangenberg, N.: Development of an information system architecture for online surgery scheduling. In Business Information Systems: 18th International Conference, BIS 2015, Poznań, Poland, June 24-26, 2015, Proceedings, W. Abramowicz, Ed. Springer International Publishing, Cham, 28–37

• Staib, J.; Grottel, S.; Gumhold, S.: Enhancing Scatterplots with Multi-Dimensional Focal Blur, EuroVis 2016, doi: 10.1111/cgf.12877

• Tiepmar J.: CTS Text Miner - Text Mining Framework based on the Canonical Text Service Protocol, In Proceedings of the 4th Workshop on the Challenges in the Management of Large Corpora p.1-7, LREC, 2016. [PDF]

• Tiepmar, J.; Eckart, T.; Goldhahn, D.; Kuras, C.: Canonical Text Services in CLARIN - Reaching out to the Digital Classics and beyond. In: CLARIN Annual Conference, 2016 [PDF]

• Tiepmar, J.; Eckart, T.; Goldhahn, D.; Kuras, C. (2017). Integrating Canonical Text Services into CLARIN's Search Infrastructure. In Linguistics and Literature Studies, 5 , 99 - 104. doi: 10.13189/lls.2017.050205 [JOURNAL]

• Tiepmar, J.: (Talk) Canonical Text Services in CLARIN - Reaching out to the Digital Classics and beyond. In: CLARIN Annual Conference, 2016 [VIDEO] [SLIDES]

• Tominski, C.; Gladisch, S.; Kister, U.; Dachselt, R.; Schumann, H.; Interactive Lenses for Visualization: An Extended Survey. In Computer Graphics Forum. 1-28, 2016.

• Ulbricht, R.; Hartmann, C.;  Hahmann, M.;  Donker, H.;  Lehner, W.: Web-based Benchmarks for Forecasting Systems: The ECAST Platform. In SIGMOD Conference, San Francisco, USA, June 26 – July 1, 2016

• Vasileios Theodorou, Alberto Abelló, Wolfgang Lehner, Maik Thiele: Concurrency and Computation: Practice and Experience 28(15): 3969-3993 (2016)

• D. Vatsalan, P. Christen, E. Rahm: Scalable privacy-preserving linking of multiple databases using Counting Bloom filters. Proc. ICDM workshop on Privacy and Discrimination in Data Mining (PDDM), 2016

• Waldherr, A.; Heyer, G.; Jähnichen, P.; Wiedemann, G.; Niekler, A.: Mining big data with computational methods. In: Political communication in the online world: Theoretical approaches and research designs., New York, Routledge, 2016

• Zeckzer, D.; Gerighausen, D.; Müller, L.: Analyzing Histone Modifications in iPS Cells Using Tiled Binned 3D Scatter Plots, International Symposium on Big Data Visual Analytics, Sydney, Australia, (2016)

• 2015

• Braunschweig, K.; Thiele, M.; Eberius, J.; Lehner, W.: Column-specific Context Extraction for Web Tables. In 30th ACM/SIGAPP Symposium on Applied Computing (SAC), Salamanca, Spain, April 13-17, 2015 [PDF]

• Braunschweig, K.; Thiele, M.;  Eberius, J; Lehner, W.: From Web Tables to Concepts: a Semantic Normalization Approach. In 34th International Conference on Conceptual Modeling (ER 2015), Stockholm, Sweden, October 19-22, 2015

• Cheema, M. F.; Blumenstein, J.; Scheuermann, G.: Modelling Concepts to Improve the Search Capabilities on Ancient Corpora. Proceedings of the Digital Humanities 2015.

• Christen, V.; Groß, A; Varghese, J.; Dugas, M.; Rahm, E.: Annotating Medical Forms using UMLS, Proc. 11th Intl. Conference on Data Integration in the Life Sciences (DILS), Los Angeles, July 2015 [PDF]

• Julian Eberius, Katrin Braunschweig, Markus Hentsch, Maik Thiele, Ahmad Ahmadov and Wolfgang Lehner: Building the Dresden Web Table Corpus: A Classification Approach. In 2nd IEEE/ACM International Symposium on Big Data Computing (BDC 2015), Limassol, Cyprus, December 7-10, 2015.

• Eberius, J.; Thiele, M; Braunschweig, K.; Lehner, W.: Top-k entity augmentation using consistent set covering. Proceedings of the 27th International Conference on Scientific and Statistical Database Management. ACM, 2015 [PDF]

• Eberius, J.; Thiele, M.; Braunschweig, K.; Lehner, W.: DrillBeyond: processing multi-result open world SQL queries. Proceedings of the 27th International Conference on Scientific and Statistical Database Management. ACM, 2015

• Gaunitz, B.; Roth, M.; Franczyk, B.: Dynamic and Scalable Real-Time Analytics in Logistics - Combining Apache Storm with Complex Event Processing for Enabling New Business Models in Logistics. In: ENASE - 10th International Conference on Evaluation of Novel Software Approaches to Software Engineering, Barcelona, 2015.

• Claudio Hartmann, Martin Hahmann, Wolfgang Lehner and Frank Rosenthal: Exploiting big data in time series forecasting: A cross-sectional approach. In IEEE International Conference on Data Science and Advanced Analytics, (DSAA 2015), Campus des Cordeliers, Paris, France, October 19-21, 2015.

• Jäkel, R.; Müller-Pfefferkorn, R.; Kluge, M.; Grunzke, R.; Nagel W.E.: Architectural Implications for Exascale based on Big Data Workflow Requirements, book on "Big Data & HPC“ (accepted)

• Junghanns, M.; Petermann, A.; Gomez, K.; Rahm, E.: GRADOOP: Scalable Graph Data Management and Analytics with Hadoop, Techn. Report, Univ. of Leipzig, June 2015 [PDF]

• Krull, A.; Brachmann, E.;  Michel, F.; Yang, M. Y.;  Gumhold, S.; Rother, C.: Learning Analysis-by-Synthesis for 6D Pose Estimation in RGB-D Images, ICCV 2015

• Kirillov, A.; Savchynskyy, B.; Schlesinger, D.; Vetrov, D.; Rother, C.: Inferring M-Best Diverse Labelings in a Single One, ICCV 2015

• Kister, U.; Reipschläger, P.; Matulic, F.; Dachselt, R.; BodyLenses – Embodied Magic Lenses and Personal Territories for Wall Displays. In Proceedings of the 2015 ACM International Conference on Interactive Tabletops and Surfaces. ITS '15, Funchal/Madeira, Portugal. ACM, 117-126, 2015.

• Klamka, K.; Dachselt, R.; Elasticcon: Elastic Controllers for Casual Interaction. In Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services. MobileHCI '15, Copenhagen, Denmark. ACM, 410-419, 2015.

• Nagel, W.E.; Jäkel, R.; Müller-Pfefferkorn, R.: Execution Environments for Big Data: Challenges for User Centric Scenarios, BDEC white paper, 2015

• Perera, K.; Hahmann, M.; Lehner, W.; Pedersen, T. B.; Thomsen, C.: Modeling Large Time Series for Efficient Approximate Query Processing. In DASFAA 2015 International Workshops. Springer, 2015

• Sehili, Z.; Kolb, L.; Borgs, C.; Schnell, R.; Rahm, E.: Privacy Preserving Record Linkage with PPJoin. GI-Fachtagung für Datenbanksysteme in Business, Technologie und Web (BTW), 2015 [PDF]

• Spangenberg, N.: Development of an information system architecture for online surgery scheduling. In Business Information Systems: 18th International Conference, BIS 2015, Poznań, Poland, June 24-26, 2015, Proceedings, W. Abramowicz, Ed. Springer International Publishing, Cham, 28–37

• Spangenberg, N.; Roth, M.; Franczyk, B.: Evaluating new approaches of big data analytics frameworks. In: 18th International Conference on Business Information Systems, Poznan, 2015.

• Staib, J.; Grottel S.; Gumhold S.: Visualization of Particle-based Data with Transparency and Ambient Occlusion, EuroVis 2015 (accepted)

• Tiepmar, J.: Release of the MySQL-based implementation of the CTS protocol, 3rd Workshop on the Challenges in the Management of Large Corpora, Lancaster [PDF]

• Theodorou, V.; Abelló, A.; Thiele, M.; Lehner, W.: POIESIS: a Tool for Quality-aware ETL Process Redesign. In Proceedings of the 18th International Conference on Extending Database Technology (EDBT), Brussels, Belgium, March 23-27, 2015 [PDF]

• Volke, S.; Zeckzer D.; Scheuermann,  G; Middendorf M.: A Visual Method for Analysis and Comparison of Search Landscapes, Genetic and Evolutionary Computation Conference (GECCO) 2015, 07/2015, Madrid, Spain, p.497--504, (2015)

• 2014

• S. Jänicke, A. Geßner, M. Büchler, G. Scheuermann.  Visualizations for Text Re-use.  Proceedings of the 5th International Conference on Information Visualization Theory and Applications, IVAPP 2014.

• Rahm, E.; Nagel, W. E. ScaDS Dresden/Leipzig: Ein serviceorientiertes Kompetenzzentrum für Big Data, Proc. GI-Jahrestagung, LNI, 2014 [PDF]

• von Zadow, U.; Büschel, W.; Langner, R.; Dachselt, R.; SleeD: Using a Sleeve Display to Interact with Touch-sensitive Display Walls. In Proceedings of the 2014 ACM International Conference on Interactive Tabletops and Surfaces. ITS '14, Dresden, Germany. ACM, 129-138, 2014.

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Veröffentlicht: Montag, 05. Oktober 2015 14:31

Big Data in Business - Workshop am 13. November 2015 

Am 13. November 2015 findet am Leipziger Standort des Big Data Kompetenzzentrum ScaDS Dresden/Leipzig ein Workshop zum Thema "Big Data in Business" statt. Das eintägige Programm bietet verschiedenen Anwendern von Big Data Technologien aus Wirtschaft und Forschung die Möglichkeit, sich über neue Erkenntnisse und Herausforderungen auszutauschen. Zum einem bekommen die Teilnehmer aus der Wirtschaft einen Einblick in aktuelle Industrie- und Forschungsprojekte und können sich mit Forschern aus dem Bereich der Datenintegration, Visualisierung und Wissensextraktion austauschen. Zum anderen stellen Wirtschaftsvertreter aktuelle Problemstellungen vor und bieten Wissenschaftlern die Möglichkeit, potentielle neue Forschungsfragen darzustellen. Wir freuen uns über spannende Vorträge von erfahrenen Referenten aus der Wirtschaft (u.a. von IBM, T-Systems, SAP und der GfK) die das Programm des Workshops bereichern.

Read more...News: Big Data in Business

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Veröffentlicht: Freitag, 02. Oktober 2015 09:20

Herbstschule für Big Data

21.-25. September 2015

Die erste einwöchige Schulung zum Thema Big Data für junge Absolventen und Studenten beschäftigte sich mit Themen, wie Machine Learning und Big-Data-Analyse. Sie wurde zudem in Zusammenarbeit mit dem Berlin Big Data Centre organisiert und gab auch Einblicke in Anwendungsgebiete, wie den Lebenswissenschaften oder den Digital Humanities.

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Veröffentlicht: Freitag, 17. Juli 2015 13:58

1. Herbstschule für Big Data

Angebot

Das Big Data Kompetenzzentrum ScaDS Dresden/Leipzig veranstaltet in der 39. Kalenderwoche zwischen dem 21.-25. September 2015 die 1. Herbstschule für Big Data. Das Angebot der Herbstschule richtet sich vornehmlich an Studenten und junge Absolventen sowie wissenschaftliche Mitarbeiter, die im weiten Feld rund um Big Data forschend tätig sind. Die Herbstschule vermittelt einerseits Grundlagen im Umgang mit großen und komplexen Datenbeständen, gibt darüber hinaus aber auch einen Überblick über aktuelle Lösungsansätze. Somit erhalten die Teilnehmer einen direkten Einblicken in aktuelle Forschungsfelder. Weiterhin besteht die  Möglichkeit zum Ideenaustausch und zur inhaltlichen Diskussion zwischen den Teilnehmern und Vortragenden.

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