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2016

  • Bach, B., Dachselt, R., Carpendale, S., Dwyer, T., Collins, C., & Lee, B. (2016). Immersive Analytics: Exploring Future Interaction and Visualization Technologies for Data Analytics. In (pp. 529–533).
  • Berto, S., Perdomo-Sabogal, A., Gerighausen, D., Qin, J., & Nowick, K. (2016). A Consensus Network of Gene Regulatory Factors in the Human Frontal Lobe. Frontiers in Genetics, 7. Retrieved from https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2016.00031
  • Braunschweig., K., Thiele., M., Koci., E., & Lehner., W. (2016). Putting Web Tables into Context. In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KDIR (pp. 158–165). SciTePress.
  • Cheema., M. F., Jänicke., S., Blumenstein., J., & Scheuermann., G. (2016). A Directed Concept Search Environment to Visually Explore Texts Related to User-defined Concept Models. In Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2016) - IVAPP (pp. 72–83). SciTePress.
  • Chris Becker, J. T. (2016). Case study: Preparing a TEI corpus for Canonical Text Services.
  • Dienst, S., & Beseler, J. (2016). AUTOMATIC ANOMALY DETECTION IN OFFSHORE WIND SCADA DATA. In .
  • Ebert, M. P., Meindl-Beinker, N. M., Gutting, T., Maenz, M., Betge, J., Schulte, N., Zhan, T., et al. (2022). Second-line therapy with nivolumab plus ipilimumab for older patients with oesophageal squamous cell cancer (RAMONA): a multicentre, open-label phase 2 trial. Lancet Healthy Longev., 3(6), e417-e427. Elsevier BV.
  • Egger, R., & Hummel, S. (2016). Lernwelt Schulweg: Sozialräumliche Annäherungen an ein Alltagsphänomen. Lernweltforschung, Lernweltforschung. Deutschland: SPRINGER VS/SPRINGER FACHMEDIEN.
  • Estrella, H. F., Umlauft, J., Schmidt, A., & Korn, M. (2016). Locating mofettes using seismic noise records from small dense arrays and matched field processing analysis in the NW Bohemia/Vogtland Region, Czech Republic. Near Surface Geophysics, 14(4), 327–335. European Association of Geoscientists & Engineers.
  • Flegel, T., Neumann, A., Holst, A.-L., Kretzschmann, O., Loderstedt, S., Tästensen, C., Gutmann, S., et al. (2024). Machine learning algorithms predict canine structural epilepsy with high accuracy. Frontiers in Veterinary Science, 11. Retrieved from https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2024.1406107
  • Fröbe, M., Günther, S., Probst, M., Potthast, M., & Hagen, M. (2022). Webis-MS-MARCO-Anchor-Texts-22. Zenodo.
  • Geanes, A. R., Cho, H. P., Nance, K. D., McGowan, K. M., Conn, P. J., Jones, C. K., Meiler, J., et al. (2016). Ligand-based virtual screen for the discovery of novel M5 inhibitor chemotypes. Bioorganic & Medicinal Chemistry Letters, 26(18), 4487–4491. Elsevier BV. Retrieved from http://dx.doi.org/10.1016/j.bmcl.2016.07.071
  • Ghiasvand, S., Ciorba, F. M., & Nagel, W. E. (2016). Turning Privacy Constraints into Syslog Analysis Advantage. In International Conference for High Performance Computing, Networking, Storage and Analysis (SC). Salt Lake City, Utah, USA. Retrieved from http://sc16.supercomputing.org/sc-archive/tech_poster/tech_poster_pages/post161.html
  • Ghiasvand, S., Ciorba, F. M., Tschuter, R., & Nagel, W. E. (2016). Lessons Learned from Spatial and Temporal Correlation of Node Failures in High Performance Computers. In Proceedings of the 24th Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP) (pp. 377–381). Heraklion, Crete, Greece: IEEE. Retrieved from http://ieeexplore.ieee.org/document/7445361/
  • Ghiasvand, S., Nagel, W. E., & Ciorba, F. M. (2016). Toward Resilience in HPC: A Prototype to Analyze and Predict System Behavior. In International Supercomputing Conference (ISC). Frankfurt, Germany.
  • Grottel, S., Krone, M., Müller, C., Reina, G., & Ertl, T. (2016). MegaMolâ„¢ - for Fun and Profit.
  • Haase, R., Andreeff, M., & Abolmaali, N. (2016). On the Reliability of Automatic Volume Delineation in Low-Contrast [18 F] FMISO-PET Imaging. Molecular Radio-Oncology, 175–187. Springer Berlin Heidelberg.
  • Hahmann, M., Hartmann, C., Kegel, L., Habich, D., & Lehner, W. (2016). Big by blocks: modular analytics:. it - Information Technology, 58.
  • Hans D. Pogrzeba, J. T. (2016). Visualisierungen für CTS Text Miner.
  • 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 Proceedings of the International Workshop Exploring Old Maps (EOM 2016), University of Luxembourg (pp. 11–12).
  • Hoehne, R., & Staib, J. (2016). Multi-scale visualisation--key to an enhanced understanding of materials. Carbon Compos Mag, 4, 20–21.
  • Hoffmann, J., Zeckzer, D., & Bogdan, M. (2016). Using FPGAs to Accelerate Myers Bit-Vector Algorithm. In E. Kyriacou, S. Christofides, & C. S. Pattichis (Eds.), XIV Mediterranean Conference on Medical and Biological Engineering and Computing 2016 (pp. 535–541). Cham: Springer International Publishing.
  • Hoffmann, N. (2016). Dynamic Thermal Imaging for Intraoperative Monitoring of Neuronal Activity and Cortical Perfusion (PhD dissertation). Dissertation, Dresden, Technische Universität Dresden, 2016.
  • Joachim Staib, R. H. et al. (2016). In Leichtbaustrukturen zoomen Plattform: Unabhängige Visualisierungssoftware vom ILK.
  • Junghanns, M., Petermann, A., Teichmann, N., Gomez, K., & Rahm, E. (2016). Analyzing Extended Property Graphs with Apache Flink. In .
  • Kegel, L., Hahmann, M., & Lehner, W. (2016). Template-based Time Series Generation with Loom. In T. Palpanas & K. Stefanidis (Eds.), Proceedings of the Workshops of the EDBT/ICDT 2016 Joint Conference, EDBT/ICDT Workshops 2016, Bordeaux, France, March 15, 2016, CEUR Workshop Proceedings (Vol. 1558). CEUR-WS.org. Retrieved from https://ceur-ws.org/Vol-1558/paper18.pdf
  • Kirillov, A., Schlesinger, D., Zheng, S., Savchynskyy, B., Torr, P. H. S., & Rother, C. (2016). Joint Training of Generic CNN-CRF Models with Stochastic Optimization. Retrieved from https://arxiv.org/abs/1511.05067
  • Kirillov, A., Shekhovtsov, A., Rother, C., & Savchynskyy, B. (2016). Joint M-Best-Diverse Labelings as a Parametric Submodular Minimization. Retrieved from https://arxiv.org/abs/1606.07015
  • Kister, U., Reipschläger, P., & Dachselt, R. (2016). 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 (pp. 139–148). Niagara Falls, Ontario, Canada: Association for Computing Machinery. Retrieved from https://doi.org/10.1145/2992154.2992168
  • Knutzen, F., Averbeck, P., Barrasso, C., Bouwer, L. M., Gardiner, B., Grünzweig, J. M., Hänel, S., et al. (2023). Impacts and damages of the European multi-year drought and heat event 2018–2022 on forests, a review.
  • Langner, R., Zadow, U., Horak, T., Mitschick, A., & Dachselt, R. (2016). Content Sharing Between Spatially-Aware Mobile Phones and Large Vertical Displays Supporting Collaborative Work. In Collaboration Meets Interactive Spaces (pp. 75–96).
  • Mendenhall, J., & Meiler, J. (2016). Improving quantitative structure–activity relationship models using Artificial Neural Networks trained with dropout. Journal of Computer-Aided Molecular Design, 30(2), 177–189. Springer Science and Business Media LLC. Retrieved from http://dx.doi.org/10.1007/s10822-016-9895-2
  • Müller, L., Gerighausen, D., Farman, M., & Zeckzer, D. (2016). Sierra platinum: a fast and robust peak-caller for replicated ChIP-seq experiments with visual quality-control and-steering. BMC bioinformatics, 17, 1–13. Springer.
  • Mustikovela, S. K., Yang, M. Y., & Rother, C. (2016). Can Ground Truth Label Propagation from Video help Semantic Segmentation?. Retrieved from https://arxiv.org/abs/1610.00731
  • Nentwig, M., Groß, A., & Rahm, E. (2016). Holistic Entity Clustering for Linked Data. In .
  • Nentwig, M., Hartung, M., Ngonga Ngomo, A.-C., & Rahm, E. (2016). A Survey of Current Link Discovery Frameworks. Semantic Web Journal, 8.
  • Perera, K., Hahmann, M., Lehner, W., Pedersen, T., & Thomsen, C. (2016). Efficient Approximate OLAP Querying Over Time Series. In (pp. 205–211).
  • Petermann, A., & Junghanns, M. (2016). Scalable business intelligence with graph collections. it - Information Technology, 58.
  • Petermann, A., Junghanns, M., Kemper, S., Gómez, K., Teichmann, N., & Rahm, E. (2016). Graph Mining for Complex Data Analytics. In 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW) (pp. 1316–1319).
  • Rahm, E. (2016). The Case for Holistic Data Integration. In .
  • Rahm, E. (2016). Big Data Analytics. it - Information Technology, 58.
  • Reckziegel, M., Jänicke, S., & Scheuermann, G. (2016). CTRaCE: Canonical Text Reader and Citation Exporter. In M. Eder & J. Rybicki (Eds.), 11th Annual International Conference of the Alliance of Digital Humanities Organizations, DH 2016, Krakow, Poland, July 11-16, 2016, Conference Abstracts (pp. 869–871). Alliance of Digital Humanities Organizations (ADHO). Retrieved from http://dh2016.adho.org/abstracts/206
  • Sauer, A. (2016). Aufbereitung, Auswertung und Visualisierung der Ergebnisse von Wasserhaushaltssimulationen für Sachsen mit ArcEGMO auf Basis von 10 alternativen Klimaprojektionen.
  • Schemala, D., Schlesinger, D., Winkler, P., Herold, H., & Meinel, G. (2016). Semantic segmentation of settlement patterns in gray-scale map images using RF and CRF within an HPC environment. In .
  • Sehili, Z., & Rahm, E. (2016). Speeding up privacy preserving record linkage for metric space similarity measures. Datenbank Spektrum, 16(3), 227–236. Springer Science and Business Media LLC.
  • Sodoge, J., Kuhlicke, C., Mahecha, M. D., & de Brito, M. M. (2024). Text mining uncovers the unique dynamics of socio-economic impacts of the 2018–2022 multi-year drought in Germany. Natural Hazards and Earth System Sciences, 24(5), 1757–1777. Copernicus GmbH. Retrieved from http://dx.doi.org/10.5194/nhess-24-1757-2024
  • Sollich, H., Zadow, U., Pietzsch, T., Tomancak, P., & Dachselt, R. (2016). Exploring Time-dependent Scientific Data Using Spatially Aware Mobiles and Large Displays. In (pp. 349–354).
  • Staib, J., Grottel, S., & Gumhold, S. (2016). Enhancing Scatterplots with Multi-Dimensional Focal Blur. Computer Graphics Forum, 35, 11–20.
  • Stützer, K., Haase, R., Lohaus, F., Barczyk, S., Exner, F., Löck, S., Rühaak, J., et al. (2016). Evaluation of a deformable registration algorithm for subsequent lung computed tomography imaging during radiochemotherapy. Medical Physics, 43(9), 5028–5039. American Association of Physicists in Medicine.
  • Tiepmar, J. (2016). CTS text miner--text mining framework based on the canonical text service protocol. In Proc. 4th LREC Workshop on Challenges in the Management of Large Corpora (pp. 1–7).
  • Tiepmar, J. (2015). Release of the MySQL based implementation of the CTS protocol. In P. Ba≈Ñski, H. Biber, E. Breiteneder, M. Kupietz, H. Lüngen, & A. Witt (Eds.), Proceedings of the 3rd Workshop on Challenges in the Management of Large Corpora (CMLC-3), Lancaster, 20 July 2015, Proceedings of the 3rd Workshop on Challenges in the Management of Large Corpora (CMLC-3), Lancaster, 20 July 2015 (pp. 35–43). Mannheim: Institut für Deutsche Sprache. Retrieved from https://nbn-resolving.org/urn:nbn:de:bsz:mh39-38374
  • Tiepmar, J., Eckart, T., Goldhahn, D., & Kuras, C. (2016). Canonical text services in CLARIN--Reaching out to the Digital Classics and beyond. In CLARIN Annual Conference.
  • Tillner, F., Thute, P., Löck, S., Dietrich, A., Fursov, A., Haase, R., Lukas, M., et al. (2016). Precise image-guided irradiation of small animals: a flexible non-profit platform. Physics in Medicine & Biology, 61(8), 3084. IOP Publishing.
  • Ulbricht, M. (2021). On the maximal number of complete extensions in abstract argumentation frameworks. In Proceedings of the Eighteenth International Conference on Principles of Knowledge Representation and Reasoning. Hanoii, Vietnam: International Joint Conferences on Artificial Intelligence Organization.
  • Ulbricht, R., Hartmann, C., Hahmann, M., Donker, H., & Lehner, W. (2016). Web-based Benchmarks for Forecasting Systems: The ECAST Platform. In (pp. 2169–2172).
  • Vatsalan, D., Christen, P., & Rahm, E. (2016). Scalable Privacy-Preserving Linking of Multiple Databases Using Counting Bloom Filters. In .
  • von Suchodoletz, H., Gärtner, A., Hoth, S., Umlauft, J., Sukhishvili, L., & Faust, D. (2016). Late Pleistocene river migrations in response to thrust belt advance and sediment-flux steering—The Kura River (southern Caucasus). Geomorphology, 266, 53–65. Elsevier.
  • Vrandev ci’c, D., Pintscher, L., & Krötzsch, M. (2023). Wikidata: The Making Of. In Y. Ding, J. Tang, J. F. Sequeda, L. Aroyo, C. Castillo, & G.-J. Houben (Eds.), Companion Proceedings of the ACM Web Conference 2023 (WWW’23) (pp. 615–624). United States of America: Association for Computing Machinery (ACM), New York.
  • Waldherr, A., Heyer, G., Jähnichen, P., Niekler, A., & Wiedemann, G. (2016). Mining Big Data With Computational Methods. In (pp. 201–217).
  • Xavier, L. C. P., da Silva, S. M. O., Carvalho, T. M. N., Filho, J. D. P., & de Assis de Souza Filho, F. (2020). Use of Machine Learning in Evaluation of Drought Perception in Irrigated Agriculture: The Case of an Irrigated Perimeter in Brazil. Water, 12(6), 1546. Multidisciplinary Digital Publishing Institute.
  • Yang, Z., Algesheimer, R., & Tessone, C. J. (2016). A Comparative Analysis of Community Detection Algorithms on Artificial Networks. Scientific Reports, 6(1). Springer Science and Business Media LLC. Retrieved from http://dx.doi.org/10.1038/srep30750
  • Zeckzer, D., Gerighausen, D., & Muller, L. (2016). Analyzing Histone Modifications in iPS Cells Using Tiled Binned 3D Scatter Plots. In 2016 Big Data Visual Analytics (BDVA) (Vol. 23, pp. 1–8). IEEE. Retrieved from http://dx.doi.org/10.1109/BDVA.2016.7787042
funded by:
Gefördert vom Bundesministerium für Bildung und Forschung.
Gefördert vom Freistaat Sachsen.