Publikationen

    • Georg Stefan Schlake, Max Pernklau, Christian Beecks: Automated Exploratory Clustering to Democratize Clustering Analysis. Applied Sciences 15(12): 6876 (2025)
    • Anne Gresch, Jana Osthues, Jan D Hüwel, Jennifer K Briggs, Tim Berger, Ruben Koch, Thomas Deickert, Christian Beecks, Richard KP Benninger, Martina Düfer: Resolving spatiotemporal electrical signaling within the islet via CMOS microelectrode arrays. Diabetes 74 (39): 343-354 (2025)
    • Kushagra Agrawal, Polat Goktas, Maike Holtkemper, Christian Beecks, Navneet Kumar: AI-driven transformation in food manufacturing: a pathway to sustainable efficiency and quality assurance. Frontiers in Nutrition 12: 1553942 (2025)
    • Max Pernklau, Nikita Averitchev, Christian Beecks: Extending K-Means Clustering with Ptolemy's Inequality. BTW 2025: 377-389
    • Alexander Graß, Rohit A. Deshmukh, Christian Beecks, Stefan Decker: Towards an Ontology for Representing Time Series Knowledge: Motivation, Requirements and Concept. CAiSE Forum 2025: 103-110
    • Maria Potanin, Maike Holtkemper, Tobias Golz, Christian Beecks: Towards a Standardized Data Science Competence Framework: A Literature Review Approach. CSEDU (2) 2025: 569-581
    • Maria Potanin, Maike Holtkemper, Simone Opel, Andrea Linxen, Christian Beecks, Tobias Golz: Implementing Learning Paths into Data Science Courses - a Qualitative Approach. EDUCON 2025: 1-3

    • Enrico Alberti, Sergio Álvarez-Napagao, Víctor Anaya, Marta Barroso, Cristian Barrué, Christian Beecks, Letizia Bergamasco, Sisay Adugna Chala, Victor Gimenez-Abalos, Alexander Graß, Daniel Hinjos, Maike Holtkemper, Natalia Jakubiak, Alexandros Nizamis, Edoardo Pristeri, Miquel Sànchez-Marrè, Georg Stefan Schlake, Jona Scholz, Gabriele Scivoletto, Stefan Walter: AI Lifecycle Zero-Touch Orchestration within the Edge-to-Cloud Continuum for Industry 5.0. Syst. 12(2): 48 (2024)
    • Andrea Linxen, Vera-Maria Schmidt, Harald Klinke, Christian Beecks: Ontology-driven knowledge base for digital humanities: Restructuring knowledge organization at the library of the Folkwang University of the Arts. IEEE Big Data 2024: 2449-2455
    • Maike Holtkemper, Christian Beecks: Empowering Data Science Teams: How Automation Frameworks Address Competency Gaps Across Project Lifecycles. IEEE Big Data 2024: 3134-3142
    • Jan David Hüwel, Georg Stefan Schlake, Kevin Albrechts, Christian Beecks: Discovering Propagating Signals in High-Content Multivariate Time Series via Spatio-Temporal Subsequence Clustering. IEEE Big Data 2024: 4153-4161
    • Georg Stefan Schlake, Max Pernklau, Christian Beecks: Automated Exploratory Clustering. IEEE Big Data 2024: 5711-5720
    • Georg Stefan Schlake, Christian Beecks: The Skyline Operator to Find the Needle in the Haystack for Automated Clustering. IEEE Big Data 2024: 6117-6122
    • Emeka Ndupuechi, Christian Beecks: Fault Detection in Transmission Production Lines Based on Imbalanced Multivariate Time Series. BigDataService 2024: 35-43
    • Jan David Hüwel, Christian Beecks: Discovering Structural Regularities in Time Series via Gaussian Processes. DSAA 2024: 1-10
    • Georg Stefan Schlake, Christian Beecks: Validating Arbitrary Shaped Clusters - A Survey. DSAA 2024: 1-12
    • Jan David Hüwel, Christian Beecks: Frequent Component Analysis for Large Time Series Databases with Gaussian Processes. EDBT 2024: 617-622
    • Christian Beecks, Alexander Graß, Anandraj Amalraj, Marc Jentsch, Felix Kitschke, Maximilian Norz, Patric Schäffer: Entwicklung einer KI für automatisierte Tierschutzkontrollen in der Schweineschlachtung. INFORMATIK 2024: 1463-1477
    • Max Pernklau, Christian Beecks: Towards Ptolemaic metric properties of the z-normalized Euclidean distance for multivariate time series indexing. ICDEW 2024: 153-157
    • Simone Opel, Andrea Linxen, Christian Beecks: What Students Should Learn and Teachers Must Know About Artificial Intelligence. IDEAL (2) 2024: 488-494
    • Alexander Graß, Christian Beecks, Stefan Decker: Structural and Semantic Data Layers in Time Series Analyses. IDEAL (1) 2024: 505-511
    • Christian Beecks, Anandraj Amalraj, Alexander Graß, Marc Jentsch, Felix Kitschke, Maximilian Norz, Patric Schäffer: Leveraging YOLO for Real-Time Video Analysis of Animal Welfare in Pig Slaughtering Processes. KI 2024: 275-281
    • Jan David Hüwel, Georg Stefan Schlake, Kevin Albrechts, Christian Beecks: Identifying Propagating Signals with Spatio-Temporal Clustering in Multivariate Time Series. SISAP 2024: 207-214
    • Andreas Besginow, Jan David Hüwel, Thomas Pawellek, Christian Beecks, Markus Lange-Hegermann: On the Laplace Approximation as Model Selection Criterion for Gaussian Processes. CoRR abs/2403.09215 (2024)

    • Alexander Graß, Christian Beecks, Sisay Adugna Chala, Christoph Lange, Stefan Decker: A Knowledge Graph for Query-Induced Analyses of Hierarchically Structured Time Series Information. ADBIS (Short Papers) 2023: 174-184
    • Andrea Linxen, Florian Endel, Simone Opel, Christian Beecks: Knowledge Graphs for Competency-Based Education. IEEE Big Data 2023: 2942-2945
    • Georg Stefan Schlake, Christian Beecks: Towards Automated Clustering. IEEE Big Data 2023: 6268-6270
    • Andrea Linxen, Simone Opel, Stephanie Ebbing, Christian Beecks: Prototyping a Virtual Tutor with Modular Teaching Styles. DELFI 2023: 56
    • Jan David Hüwel, Christian Beecks: Gaussian Process Component Mining with the Apriori Algorithm. DEXA (2) 2023: 423-429
    • Md. Rezaul Karim, Md Shajalal, Alexander Graß, Till Döhmen, Sisay Adugna Chala, Alexander Boden, Christian Beecks, Stefan Decker: Interpreting Black-box Machine Learning Models for High Dimensional Datasets. DSAA 2023: 1-10
    • Maike Holtkemper, Maria Potanin, Alexander Oberst, Christian Beecks: Risk Identification of Data Science Projects: A Literature Review. LWDA 2023: 1-13

    • Fabian Berns, Jan David Hüwel, Christian Beecks: Automated Model Inference for Gaussian Processes: An Overview of State-of-the-Art Methods and Algorithms. SN Comput. Sci. 3(4): 300 (2022)
    • Jan David Hüwel, Anne Gresch, Tim Berger, Martina Düfer, Christian Beecks: Analysis of Extracellular Potential Recordings by High-Density Micro-electrode Arrays of Pancreatic Islets. DEXA (2) 2022: 270-276
    • Jan David Hüwel, Anne Gresch, Fabian Berns, Ruben Koch, Martina Düfer, Christian Beecks: Tracing Patterns in Electrophysiological Time Series Data. DSAA 2022: 1-10
    • Georg Stefan Schlake, Jan David Hüwel, Fabian Berns, Christian Beecks: Evaluating the Lottery Ticket Hypothesis to Sparsify Neural Networks for Time Series Classification. ICDE Workshops 2022: 70-73
    • Till Döhmen, Madelon Hulsebos, Christian Beecks, Sebastian Schelter: GitSchemas: A Dataset for Automating Relational Data Preparation Tasks. ICDE Workshops 2022: 74-78
    • Alexander Graß, Till Döhmen, Christian Beecks: Sample-based Kernel Structure Learning with Deep Neural Networks for Automated Structure Discovery. ICDE Workshops 2022: 79-83
    • Christian Beecks, Fabian Berns, Jan David Hüwel, Andrea Linxen, Georg Stefan Schlake, Tim Düsterhus: A Comparative Performance Analysis of Fast K-Means Clustering Algorithms. iiWAS 2022: 119-125
    • Jan David Hüwel, Florian Haselbeck, Dominik G. Grimm, Christian Beecks: Dynamically Self-adjusting Gaussian Processes for Data Stream Modelling. KI 2022: 96-114
    • Md. Rezaul Karim, Md Shajalal, Alexander Graß, Till Döhmen, Sisay Adugna Chala, Christian Beecks, Stefan Decker: Interpreting Black-box Machine Learning Models for High Dimensional Datasets. CoRR abs/2208.13405 (2022)

    • Jan David Hüwel, Fabian Berns, Christian Beecks: Automated Kernel Search for Gaussian Processes on Data Streams. IEEE BigData 2021: 3584-3588
    • Fabian Berns, Jan David Hüwel, Christian Beecks: LOGIC: Probabilistic Machine Learning for Time Series Classification. ICDM 2021: 1000-1005
    • Jan David Hüwel, Andreas Besginow, Fabian Berns, Markus Lange-Hegermann, Christian Beecks: On Kernel Search Based Gaussian Process Anomaly Detection. IN4PL (Revised Selected Papers) 2021: 1-23
    • Sergio Álvarez-Napagao, Boki Ashmore, Marta Barroso, Cristian Barrué, Christian Beecks, Fabian Berns, Ilaria Bosi, Sisay Adugna Chala, Nicola Ciulli, Marta Garcia-Gasulla, Alexander Grass, Dimosthenis Ioannidis, Natalia Jakubiak, Karl Köpke, Ville Lämsä, Pedro Megias, Alexandros Nizamis, Claudio Pastrone, Rosaria Rossini, Miquel Sànchez-Marrè, Luca Ziliotti: knowlEdge Project -Concept, Methodology and Innovations for Artificial Intelligence in Industry 4.0. INDIN 2021: 1-7
    • Fabian Berns, Christian Beecks: Stochastic Time Series Representation for Interval Pattern Mining via Gaussian Processes. SDM 2021: 10-18
    • Fabian Berns, Christian Beecks: Complexity-Adaptive Gaussian Process Model Inference for Large-Scale Data. SDM 2021: 360-368
    • Fabian Berns, Joschka Hannes Strueber, Christian Beecks: Local Gaussian Process Model Inference Classification for Time Series Data. SSDBM 2021: 209-213

    • Berns F, Beecks C. ‘Automatic Gaussian Process Model Retrieval for Big Data.’ In Proceedings of the ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, 2020. doi: 10.1145/3340531.3412182.
    • Berns F, Beecks C. ‘Towards Large-scale Gaussian Process Models for Efficient Bayesian Machine Learning.’ In Proceedings of the 9th International Conference on Data Science, Technology and Applications, 2020. doi: 10.5220/0009874702750282.
    • Berns F, Beecks C. ‘Large-scale Retrieval of Bayesian Machine Learning Models for Time Series Data via Gaussian Processes.’ In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, 71-80: SciTePress, 2020. doi: 10.5220/0010109700710080.
    • Berns F, Schmidt K, Bracht I, Beecks C. ‘3CS Algorithm for Efficient Gaussian Process Model Retrieval.’ In Proceedings of the 25th International Conference on Pattern Recognition 2020, 1773-1780.: IEEE Computer Society. 2020, doi: 10.1109/ICPR48806.2021.9412805.
    • Berns F, Ramsdorf T, Beecks C. ‘Machine Learning for Storage Location Prediction in Industrial High Bay Warehouses.’ In 1st International Workshop on Industrial Machine Learning at 25th International Conference on Pattern Recognition 2020, 650-661.: Springer, 2020, doi: 10.1007/978-3-030-68799-1_47.
    • Berns F, Lange-Hegermann M, Beecks C. ‘Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0.’ In Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - Volume 1: IN4PL,, 87-92.: SciTePress, 2020. doi: 10.5220/0010130300870092.
    • Pandian V P S, Suleri S, Beecks C, Jarke M. ‘MetaMorph: AI Assistance to Transform Lo-Fi Sketches to Higher Fidelities‘. In Proceedings 32nd Australian Conference on Human-Computer-Interaction 2020, Sydney, Australia, 403-412. doi: 10.1145/3441000.3441030.

    • Beecks C, Berns F, Schmidt KW. ‘Ptolemaic Indexing for Managing and Querying Internet of Things (IoT) Data.’ In 2019 IEEE International Conference on Big Data (Big Data), 4148-4151.: IEEE. doi: 10.1109/BigData47090.2019.9005725.
    • Beecks C, Schmidt KW, Berns F, Grass A. ‘Gaussian Processes for Anomaly Description in Production Environments.’ In Proceedings of the Workshops of the Joint Conference on Extending Database Technology and Database Theory, EDBT/ICDT 2019, Lisbon, Portugal, March 26, 2019.: CEUR-WS.org.
    • Berns F, Rossetto L, Schoeffmann K, Beecks C, Awad G. ‘V3C1 Dataset: An Evaluation of Content Characteristics.’ In Proceedings of the 2019 on International Conference on Multimedia Retrieval, ICMR 2019, Ottawa, ON, Canada, June 10-13, 2019, edited by El-Saddik A, Bimbo AD, Zhang Z, Hauptmann AG, Candan KS et al., 334-338.: ACM. doi: 10.1145/3323873.3325051.
    • Berns F, Schmidt K, Grass A, Beecks C. ‘A New Approach for Efficient Structure Discovery in IoT.’ In 2019 IEEE International Conference on Big Data (Big Data), 4152-4156.: IEEE. doi: 10.1109/BigData47090.2019.9006082.
    • Leibetseder A, Münzer B, Primus MJ, Kletz S, Schoeffmann K, Berns F, Beecks C. ‘lifeXplore at the Lifelog Search Challenge 2019.’ In Proceedings of the ACM Workshop on Lifelog Search Challenge, LSC@ICMR 2019, Ottawa, ON, Canada, 10 June 2019, edited by Gurrin C, Schöffmann K, Joho H, Dang-Nguyen D, Riegler M, Piras L, 13-17.: ACM. doi: 10.1145/3326460.3329157.
    • Sandfort F, Strieth-Kalthoff F, Kühnemund M, Beecks C, Glorius F. ‘A Structure-Based Platform for Predicting Chemical Reactivity.’ ChemRxiv 2019. doi: 10.26434/chemrxiv.9981488.v1.

    • Beecks C, Berrendorf M. ‘Optimal k-Nearest-Neighbor Query Processing via Multiple Lower Bound Approximations.’ In IEEE International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018, 614-623. doi: 10.1109/BigData.2018.8622493.
    • Beecks C, Devasya S, Schlutter R. ‘Machine Learning for Enhanced Waste Quantity Reduction: Insights from the MONSOON Industry 4.0 Project.’ In Selected papers from the International Conference on Machine Learning for Cyber Physical Systems, ML4CPS 2018, Karlsruhe, Germany, October 23-24, 1-6.: Springer, 2018. doi: 10.1007/978-3-662-58485-9\_1.
    • Beecks C, Grass A. ‘Efficient Point-Based Pattern Search in 3D Motion Capture Databases.’ In 6th IEEE International Conference on Future Internet of Things and Cloud, FiCloud 2018, Barcelona, Spain, August 6-8, 2018, edited by Younas M, Disso JP, 230-235.: IEEE Computer Society. doi: 10.1109/FiCloud.2018.00041.
    • Beecks C, Grass A, Devasya S. ‘Metric Indexing for Efficient Data Access in the Internet of Things.’ In IEEE International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018, 5132-5136. doi: 10.1109/BigData.2018.8622387.
    • Grass A, Beecks C, Soto JAC. ‘Unsupervised Anomaly Detection in Production Lines.’ In Selected papers from the International Conference on Machine Learning for Cyber Physical Systems, ML4CPS 2018, Karlsruhe, Germany, October 23-24, 2018, 18-25.: Springer. doi: 10.1007/978-3-662-58485-9\_3.
    • Schoeffmann K, Husslein H, Kletz S, Petscharnig S, Münzer B, Beecks C. ‘Video retrieval in laparoscopic video recordings with dynamic content descriptors.’ Multimedia Tools Appl. 77, No. 13: 16813-16832, 2018. doi: 10.1007/s11042-017-5252-2.

    • Beecks C, Borutta F, Kröger P, Seidl T (Eds.): Similarity Search and Applications - 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings. : Springer. doi: 10.1007/978-3-319-68474-1.
    • Beecks C, Kletz S, Schoeffmann K. ‘Large-Scale Endoscopic Image and Video Linking with Gradient-Based Signatures.’ In Third IEEE International Conference on Multimedia Big Data, BigMM 2017, Laguna Hills, CA, USA, April 19-21, 2017, 17-21.: IEEE Computer Society. doi: 10.1109/BigMM.2017.44.
    • Münzer B, Primus MJ, Hudelist MA, Beecks C, Hürst W, Schoeffmann K. ‘When content-based video retrieval and human computation unite: Towards effective collaborative video search.’ In 2017 IEEE International Conference on Multimedia & Expo Workshops, ICME Workshops, Hong Kong, China, July 10-14, 2017, 214-219.: IEEE Computer Society. doi: 10.1109/ICMEW.2017.8026262.
    • Schüller D, Beecks C, Hassani M, Hinnell J, Brenger B, Seidl T, Mittelberg I. ‘Automated Pattern Analysis in Gesture Research: Similarity Measuring in 3D Motion Capture Models of Communicative Action.’ Digital Humanities Quarterly 11, No. 2, 2017.

    • Beecks C, Grass A. ‘Multi-step threshold algorithm for efficient feature-based query processing in large-scale multimedia databases.’ In 2016 IEEE International Conference on Big Data, BigData 2016, Washington DC, USA, December 5-8, 2016, edited by Joshi J, Karypis G, Liu L, Hu X, Ak R et al., 596-605.: IEEE. doi: 10.1109/BigData.2016.7840652.
    • Beecks C, Hassani M, Brenger B, Hinnell J, Schüller D, Mittelberg I, Seidl T. ‘Efficient Query Processing in 3D Motion Capture Gesture Databases.’ Int. J. Semantic Computing 10, No. 1: 5-26, 2016. doi: 10.1142/S1793351X16400018.
    • Beecks C, Uysal MS, Seidl T. ‘Distance-based Multimedia Indexing.’ In Proceedings of the 19th International Conference on Extending Database Technology, EDBT 2016, Bordeaux, France, March 15-16, 2016, Bordeaux, France, March 15-16, 2016., edited by Pitoura E, Maabout S, Koutrika G, Marian A, Tanca L, Manolescu I, Stefanidis K, 722-723.: OpenProceedings.org. doi: 10.5441/002/edbt.2016.105.
    • Hudelist MA, Beecks C, Schoeffmann K. ‘Finding the chameleon in your video collection.’ In Proceedings of the 7th International Conference on Multimedia Systems, MMSys 2016, Klagenfurt, Austria, May 10-13, 2016, edited by Timmerer C, 31:1-31:4.: ACM. doi: 10.1145/2910017.2910631.
    • Hudelist MA, Cobarzan C, Beecks C, Werken R, Kletz S, Hürst W, Schoeffmann K. ‘Collaborative Video Search Combining Video Retrieval with Human-Based Visual Inspection.’ In MultiMedia Modeling - 22nd International Conference, MMM 2016, Miami, FL, USA, January 4-6, 2016, Proceedings, Part II, edited by Tian Q, Sebe N, Qi G, Huet B, Hong R, Liu X, 400-405.: Springer. doi: 10.1007/978-3-319-27674-8_40.
    • Hürst W, Ching AIV, Hudelist MA, Primus MJ, Schoeffmann K, Beecks C. ‘A New Tool for Collaborative Video Search via Content-based Retrieval and Visual Inspection.’ In Proceedings of the 2016 ACM Conference on Multimedia Conference, MM 2016, Amsterdam, The Netherlands, October 15-19, 2016, edited by Hanjalic A, Snoek C, Worring M, Bulterman DCA, Huet B et al., 731-732.: ACM. doi: 10.1145/2964284.2973824.
    • Nies TD, Beecks C, Godin F, Neve WD, Stepien G et al. ‘Normalized Semantic Web Distance.’ In The Semantic Web. Latest Advances and New Domains - 13th International Conference, ESWC 2016, Heraklion, Crete, Greece, May 29 - June 2, 2016, Proceedings, edited by Sack H, Blomqvist E, d'Aquin M, Ghidini C, Ponzetto SP, Lange C, 69-84.: Springer. doi: 10.1007/978-3-319-34129-3_5.
    • Nies TD, Beecks C, Godin F, Neve WD, Stepien G et al. ‘A Distance-Based Approach for Semantic Dissimilarity in Knowledge Graphs.’ In Tenth IEEE International Conference on Semantic Computing, ICSC 2016, Laguna Hills, CA, USA, February 4-6, 2016, 254-257.: IEEE Computer Society. doi: 10.1109/ICSC.2016.55.
    • Schoeffmann K, Beecks C, Lux M, Uysal MS, Seidl T. ‘Content-based retrieval in videos from laparoscopic surgery.’ In Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, San Diego, California, United States, 27 February - 3 March 2016, edited by Webster RJ, Yaniv ZR, 97861V.: SPIE. doi: 10.1117/12.2216864.
    • Uysal MS, Beecks C, Sabinasz D, Schmücking J, Seidl T. ‘Efficient Query Processing using the Earth's Mover Distance in Video Databases.’ In Proceedings of the 19th International Conference on Extending Database Technology, EDBT 2016, Bordeaux, France, March 15-16, 2016, Bordeaux, France, March 15-16, 2016., edited by Pitoura E, Maabout S, Koutrika G, Marian A, Tanca L, Manolescu I, Stefanidis K, 389-400.: OpenProceedings.org. doi: 10.5441/002/edbt.2016.36.
    • Vocht LD, Beecks C, Verborgh R, Mannens E, Seidl T, Walle RV. ‘Effect of Heuristics on Serendipity in Path-Based Storytelling with Linked Data.’ In Human Interface and the Management of Information: Information, Design and Interaction - 18th International Conference, HCI International 2016 Toronto, Canada, July 17-22, 2016, Proceedings, Part I, edited by Yamamoto S, 238-251.: Springer. doi: 10.1007/978-3-319-40349-6_23.

    • Beecks C, Hassani M, Hinnell J, Schüller D, Brenger B, Mittelberg I, Seidl T. ‘Spatiotemporal Similarity Search in 3D Motion Capture Gesture Streams.’ In Advances in Spatial and Temporal Databases - 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings, edited by Claramunt C, Schneider M, Wong RC, Xiong L, Loh W, Shahabi C, Li K, 355-372.: Springer. doi: 10.1007/978-3-319-22363-6_19.
    • Beecks C, Hassani M, Obeloer F, Seidl T. ‘Efficient Query Processing in 3D Motion Capture Databases via Lower Bound Approximation of the Gesture Matching Distance.’ In 2015 IEEE International Symposium on Multimedia, ISM 2015, Miami, FL, USA, December 14-16, 2015, 148-153.: IEEE Computer Society. doi: 10.1109/ISM.2015.86.
    • Beecks C, Hassani M, Obeloer F, Seidl T. ‘Efficient Distance-Based Gestural Pattern Mining in Spatiotemporal 3D Motion Capture Databases.’ In IEEE International Conference on Data Mining Workshop, ICDMW 2015, Atlantic City, NJ, USA, November 14-17, 2015, 1425-1432.: IEEE Computer Society. doi: 10.1109/ICDMW.2015.194.
    • Beecks C, Schoeffmann K, Lux M, Uysal MS, Seidl T. ‘Endoscopic Video Retrieval: A Signature-Based Approach for Linking Endoscopic Images with Video Segments.’ In 2015 IEEE International Symposium on Multimedia, ISM 2015, Miami, FL, USA, December 14-16, 2015, 33-38.: IEEE Computer Society. doi: 10.1109/ISM.2015.21.
    • Beecks C, Uysal MS, Hermanns J, Seidl T. ‘Gradient-based Signatures for Efficient Similarity Search in Large-scale Multimedia Databases.’ In Proceedings of the 24th ACM International Conference on Information and Knowledge Management, CIKM 2015, Melbourne, VIC, Australia, October 19 - 23, 2015, edited by Bailey J, Moffat A, Aggarwal CC, Rijke M, Kumar R et al., 1241-1250.: ACM. doi: 10.1145/2806416.2806459.
    • Beecks C, Uysal MS, Seidl T. ‘Content-Based Image Retrieval with Gaussian Mixture Models.’ In MultiMedia Modeling - 21st International Conference, MMM 2015, Sydney, NSW, Australia, January 5-7, 2015, Proceedings, Part I, edited by He X, Luo S, Tao D, Xu C, Yang J, Hasan MA, 294-305.: Springer. doi: 10.1007/978-3-319-14445-0_26.
    • Beecks C, Uysal MS, Seidl T. ‘Gradient-based signatures for big multimedia data.’ In 2015 IEEE International Conference on Big Data, Big Data 2015, Santa Clara, CA, USA, October 29 - November 1, 2015, 2834-2835.: IEEE. doi: 10.1109/BigData.2015.7364093.
    • Beecks C, Uysal MS, Seidl T. ‘Distance-based Multimedia Indexing.’ In Datenbanksysteme für Business, Technologie und Web (BTW 2015) - Workshopband, 2.-3. März 2015, Hamburg, Germany, edited by Ritter N, Henrich A, Lehner W, Thor A, Friedrich S, Wingerath W, 265-268.: GI.
    • Beecks C, Uysal MS, Seidl T. ‘Earth Mover's Distance vs. Quadratic form Distance: An Analytical and Empirical Comparison.’ In 2015 IEEE International Symposium on Multimedia, ISM 2015, Miami, FL, USA, December 14-16, 2015, 233-236.: IEEE Computer Society. doi: 10.1109/ISM.2015.76.
    • Hassani M, Beecks C, Töws D, Seidl T. ‘Mining Sequential Patterns of Event Streams in a Smart Home Application.’ In Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB, Trier, Germany, October 7-9, 2015., edited by Bergmann R, Görg S, Müller G, 159-170.: CEUR-WS.org.
    • Hassani M, Beecks C, Töws D, Serbina T, Haberstroh M et al. ‘Sequential Pattern Mining of Multimodal Streams in the Humanities.’ In Datenbanksysteme für Business, Technologie und Web (BTW), 16. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS), 4.-6.3.2015 in Hamburg, Germany. Proceedings, edited by Seidl T, Ritter N, Schöning H, Sattler K, Härder T, Friedrich S, Wingerath W, 683-686.: GI.
    • Töws D, Hassani M, Beecks C, Seidl T. ‘Optimizing Sequential Pattern Mining Within Multiple Streams.’ In Datenbanksysteme für Business, Technologie und Web (BTW 2015) - Workshopband, 2.-3. März 2015, Hamburg, Germany, edited by Ritter N, Henrich A, Lehner W, Thor A, Friedrich S, Wingerath W, 223-232.: GI.
    • Uysal MS, Beecks C, Sabinasz D, Seidl T. ‘Large-scale Efficient and Effective Video Similarity Search.’ In Proceedings of the 2015 Workshop on Large-Scale and Distributed System for Information Retrieval, LSDS-IR 2015, Melbourne, Australia, October 23, 2015, edited by Altingovde IS, Cambazoglu BB, Tonellotto N, 3-8.: ACM. doi: 10.1145/2809948.2809950.
    • Uysal MS, Beecks C, Sabinasz D, Seidl T. ‘Effective Content-Based Near-Duplicate Video Detection.’ In 2015 IEEE International Symposium on Multimedia, ISM 2015, Miami, FL, USA, December 14-16, 2015, 254-257.: IEEE Computer Society. doi: 10.1109/ISM.2015.60.
    • Uysal MS, Beecks C, Sabinasz D, Seidl T. ‘FELICITY: A Flexible Video Similarity Search Framework Using the Earth Mover's Distance.’ In Similarity Search and Applications - 8th International Conference, SISAP 2015, Glasgow, UK, October 12-14, 2015, Proceedings, edited by Amato G, Connor RCH, Falchi F, Gennaro C, 347-350.: Springer. doi: 10.1007/978-3-319-25087-8_34.
    • Uysal MS, Beecks C, Schmücking J, Seidl T. ‘Efficient similarity search in scientific databases with feature signatures.’ In Proceedings of the 27th International Conference on Scientific and Statistical Database Management, SSDBM '15, La Jolla, CA, USA, June 29 - July 1, 2015, edited by Gupta A, Rathbun SL, 30:1-30:12.: ACM. doi: 10.1145/2791347.2791384.
    • Uysal MS, Beecks C, Seidl T. ‘On efficient content-based near-duplicate video detection.’ In 13th International Workshop on Content-Based Multimedia Indexing, CBMI 2015, Prague, Czech Republic, June 10-12, 2015, 1-6.: IEEE. doi: 10.1109/CBMI.2015.7153633.
    • Vocht LD, Beecks C, Verborgh R, Seidl T, Mannens E, Walle RV. ‘Improving Semantic Relatedness in Paths for Storytelling with Linked Data on the Web.’ In The Semantic Web: ESWC 2015 Satellite Events - ESWC 2015 Satellite Events Portorož, Slovenia, May 31 - June 4, 2015, Revised Selected Papers, edited by Gandon F, Guéret C, Villata S, Breslin JG, Faron-Zucker C, Zimmermann A, 31-35.: Springer. doi: 10.1007/978-3-319-25639-9_6.

    • Beecks C, Kirchhoff S, Seidl T. ‘On the Stability of Signature-Based Distance Functions for Content-Based Image Retrieval.’ In Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014., edited by Seidl T, Hassani M, Beecks C, 226.: CEUR-WS.org.
    • Beecks C, Kirchhoff S, Seidl T. ‘On stability of signature-based similarity measures for content-based image retrieval.’ Multimedia Tools Appl. 71, No. 1: 349-362, 2014. doi: 10.1007/s11042-012-1334-3.
    • Godin F, Nies TD, Beecks C, Vocht LD, Neve WD et al. ‘The Normalized Freebase Distance.’ In The Semantic Web: ESWC 2014 Satellite Events - ESWC 2014 Satellite Events, Anissaras, Crete, Greece, May 25-29, 2014, Revised Selected Papers, edited by Presutti V, Blomqvist E, Troncy R, Sack H, Papadakis I, Tordai A, 218-221.: Springer. doi: 10.1007/978-3-319-11955-7_22.
    • Nies TD, Beecks C, Neve WD, Seidl T, Mannens E, Walle RV. ‘Towards Named-Entity-based Similarity Measures: Challenges and Opportunities.’ In Proceedings of the 7th International Workshop on Exploiting Semantic Annotations in Information Retrieval, ESAIR '14, Shanghai, China, November 7, 2014, edited by Alonso O, Kamps J, Karlgren J, 9-11.: ACM. doi: 10.1145/2663712.2666194.
    • Seidl T, Hassani M, Beecks C (Eds.): Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014. : CEUR-WS.org.
    • Uysal MS, Beecks C, Schmücking J, Seidl T. ‘Efficient Filter Approximation Using the Earth Mover's Distance in Very Large Multimedia Databases with Feature Signatures.’ In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, CIKM 2014, Shanghai, China, November 3-7, 2014, edited by Li J, Wang XS, Garofalakis MN, Soboroff I, Suel T, Wang M, 979-988.: ACM. doi: 10.1145/2661829.2661877.
    • Uysal MS, Beecks C, Seidl T. ‘On Efficient Query Processing with the Earth Mover's Distance.’ In Proceedings of the 7th Workshop on Ph.D Students, PIKM@CIKM 2014, Shanghai, China, November 3, 2014, edited by Melo G, Kacimi M, Varde AS, 25-32.: ACM. doi: 10.1145/2663714.2668047.

    • Beecks C. Distance based similarity models for content based multimedia retrieval Doctoral Thesis, 2013, RWTH Aachen University.
    • Beecks C, Kirchhoff S, Seidl T. ‘Signature matching distance for content-based image retrieval.’ In International Conference on Multimedia Retrieval, ICMR'13, Dallas, TX, USA, April 16-19, 2013, edited by Jain R, Prabhakaran B, Worring M, Smith JR, Chua T, 41-48.: ACM. doi: 10.1145/2461466.2461474.
    • Beecks C, Uysal MS, Driessen P, Seidl T. ‘Content-based exploration of multimedia databases.’ In 11th International Workshop on Content-Based Multimedia Indexing, CBMI 2013, Veszprém, Hungary, June 17-19, 2013, 59-64.: IEEE. doi: 10.1109/CBMI.2013.6576553.
    • Hetland ML, Skopal T, Lokoc J, Beecks C. ‘Ptolemaic access methods: Challenging the reign of the metric space model.’ Inf. Syst. 38, 2013, No. 7: 989-1006. doi: 10.1016/j.is.2012.05.011.

    • Beecks C, Seidl T. ‘On Stability of Adaptive Similarity Measures for Content-Based Image Retrieval.’ In Advances in Multimedia Modeling - 18th International Conference, MMM 2012, Klagenfurt, Austria, January 4-6, 2012. Proceedings, edited by Schoeffmann K, Mérialdo B, Hauptmann AG, Ngo C, Andreopoulos Y, Breiteneder C, 346-357.: Springer. doi: 10.1007/978-3-642-27355-1_33.
    • Ivanescu AM, Wichterich M, Beecks C, Seidl T. ‘The ClasSi coefficient for the evaluation of ranking quality in the presence of class similarities.’ Frontiers Comput. Sci. 6, 2012, No. 5: 568-580. doi: 10.1007/s11704-012-1175-2.
    • Krulis M, Skopal T, Lokoc J, Beecks C. ‘Combining CPU and GPU architectures for fast similarity search.’ Distributed and Parallel Databases 30, 2012, No. 3-4: 179-207. doi: 10.1007/s10619-012-7092-4.

    • Beecks C, Assent I, Seidl T. ‘Content-Based Multimedia Retrieval in the Presence of Unknown User Preferences.’ In Advances in Multimedia Modeling - 17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part I, edited by Lee K, Tsai W, Liao HM, Chen T, Hsieh J, Tseng C, 140-150.: Springer. doi: 10.1007/978-3-642-17832-0_14.
    • Beecks C, Ivanescu AM, Kirchhoff S, Seidl T. ‘Modeling image similarity by Gaussian mixture models and the Signature Quadratic Form Distance.’ In IEEE International Conference on Computer Vision, ICCV 2011, Barcelona, Spain, November 6-13, 2011, edited by Metaxas DN, Quan L, Sanfeliu A, Gool LJV, 1754-1761.: IEEE Computer Society. doi: 10.1109/ICCV.2011.6126440.
    • Beecks C, Ivanescu AM, Kirchhoff S, Seidl T. ‘Modeling multimedia contents through probabilistic feature signatures.’ In Proceedings of the 19th International Conference on Multimedia 2011, Scottsdale, AZ, USA, November 28 - December 1, 2011, edited by Candan KS, Panchanathan S, Prabhakaran B, Sundaram H, Feng W, Sebe N, 1433-1436.: ACM. doi: 10.1145/2072298.2072033.
    • Beecks C, Ivanescu AM, Seidl T, Martin D, Pischke P, Kneer R. ‘Applying similarity search for the investigation of the fuel injection process.’ In Fourth International Conference on Similarity Search and Applications, SISAP 2011, Lipari Island, Italy, June 30 - July 01, 2011, edited by Ferro A, 117-118.: ACM. doi: 10.1145/1995412.1995436.
    • Beecks C, Lokoc J, Seidl T, Skopal T. ‘Indexing the signature quadratic form distance for efficient content-based multimedia retrieval.’ In Proceedings of the 1st International Conference on Multimedia Retrieval, ICMR 2011, Trento, Italy, April 18 - 20, 2011, edited by Natale FGBD, Bimbo AD, Hanjalic A, Manjunath BS, Satoh S, 24.: ACM. doi: 10.1145/1991996.1992020.
    • Beecks C, Seidl T. ‘Analyzing the inner workings of the Signature Quadratic Form Distance.’ In Proceedings of the 2011 IEEE International Conference on Multimedia and Expo, ICME 2011, 11-15 July, 2011, Barcelona, Catalonia, Spain, 1-6.: IEEE Computer Society. doi: 10.1109/ICME.2011.6012243.
    • Beecks C, Uysal MS, Seidl T. ‘L2-Signature Quadratic Form Distance for Efficient Query Processing in Very Large Multimedia Databases.’ In Advances in Multimedia Modeling - 17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part I, edited by Lee K, Tsai W, Liao HM, Chen T, Hsieh J, Tseng C, 381-391.: Springer. doi: 10.1007/978-3-642-17832-0_36.
    • Krulis M, Lokoc J, Beecks C, Skopal T, Seidl T. ‘Processing the signature quadratic form distance on many-core GPU architectures.’ In Proceedings of the 20th ACM Conference on Information and Knowledge Management, CIKM 2011, Glasgow, United Kingdom, October 24-28, 2011, edited by Macdonald C, Ounis I, Ruthven I, 2373-2376.: ACM. doi: 10.1145/2063576.2063970.
    • Lokoc J, Beecks C, Seidl T, Skopal T. ‘Parameterized earth mover's distance for efficient metric space indexing.’ In Fourth International Conference on Similarity Search and Applications, SISAP 2011, Lipari Island, Italy, June 30 - July 01, 2011, edited by Ferro A, 121-122.: ACM. doi: 10.1145/1995412.1995438.
    • Lokoc J, Hetland ML, Skopal T, Beecks C. ‘Ptolemaic indexing of the signature quadratic form distance.’ In Fourth International Conference on Similarity Search and Applications, SISAP 2011, Lipari Island, Italy, June 30 - July 01, 2011, edited by Ferro A, 9-16.: ACM. doi: 10.1145/1995412.1995417.
    • Schoeffmann K, Ahlströ}m D, Beecks C. ‘3D Image Browsing on Mobile Devices.’ In 2011 IEEE International Symposium on Multimedia, ISM 2011, Dana Point, CA, USA, December 5-7, 2011, 335-336.: IEEE Computer Society. doi: 10.1109/ISM.2011.60.

    • Beecks C, Driessen P, Seidl T. ‘Index support for content-based multimedia exploration.’ In Proceedings of the 18th International Conference on Multimedia 2010, Firenze, Italy, October 25-29, 2010, edited by Bimbo AD, Chang S, Smeulders AWM, 999-1002.: ACM. doi: 10.1145/1873951.1874134.
    • Beecks C, Stadelmann T, Freisleben B, Seidl T. ‘Visual speaker model exploration.’ In Proceedings of the 2010 IEEE International Conference on Multimedia and Expo, ICME 2010, 19-23 July 2010, Singapore, 727-728.: IEEE Computer Society. doi: 10.1109/ICME.2010.5583176.
    • Beecks C, Uysal MS, Seidl T. ‘Similarity matrix compression for efficient signature quadratic form distance computation.’ In Third International Workshop on Similarity Search and Applications, SISAP 2010, 18-19 September 2010, Istanbul, Turkey, edited by Ciaccia P, Patella M, 109-114.: ACM. doi: 10.1145/1862344.1862361.
    • Beecks C, Uysal MS, Seidl T. ‘Signature Quadratic Form Distance.’ In Proceedings of the 9th ACM International Conference on Image and Video Retrieval, CIVR 2010, Xi'an, China, July 5-7, 2010, edited by Li S, Gao X, Sebe N, 438-445.: ACM. doi: 10.1145/1816041.1816105.
    • Beecks C, Uysal MS, Seidl T. ‘A comparative study of similarity measures for content-based multimedia retrieval.’ In Proceedings of the 2010 IEEE International Conference on Multimedia and Expo, ICME 2010, 19-23 July 2010, Singapore, 1552-1557.: IEEE Computer Society. doi: 10.1109/ICME.2010.5582949.
    • Beecks C, Uysal MS, Seidl T. ‘Efficient k-nearest neighbor queries with the Signature Quadratic Form Distance.’ In Workshops Proceedings of the 26th International Conference on Data Engineering, ICDE 2010, March 1-6, 2010, Long Beach, California, USA, 10-15.: IEEE Computer Society. doi: 10.1109/ICDEW.2010.5452772.
    • Beecks C, Wiedenfeld S, Seidl T. ‘Improving the Efficiency of Content-Based Multimedia Exploration.’ In 20th International Conference on Pattern Recognition, ICPR 2010, Istanbul, Turkey, 23-26 August 2010, 3163-3166.: IEEE Computer Society. doi: 10.1109/ICPR.2010.774.

    • Beecks C, Uysal MS, Seidl T. ‘Signature quadratic form distances for content-based similarity.’ In Proceedings of the 17th International Conference on Multimedia 2009, Vancouver, British Columbia, Canada, October 19-24, 2009, edited by Gao W, Rui Y, Hanjalic A, Xu C, Steinbach EG, El-Saddik A, Zhou MX, 697-700.: ACM. doi: 10.1145/1631272.1631391.
    • Beecks C, Wichterich M, Seidl T. „Metrische Anpassung der Earth Mover's Distanz zur Ähnlichkeitssuche in Multimedia-Datenbanken.“ In Datenbanksysteme in Business, Technologie und Web (BTW 2009), 13. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS), Proceedings, 2.-6. März 2009, Münster, Germany, herausgegeben von Freytag JC, Ruf T, Lehner W, Vossen G, 207-216.: GI.
    • Wichterich M, Beecks C, Sundermeyer M, Seidl T. ‘Relevance Feedback for the Earth Mover's Distance.’ In Adaptive Multimedia Retrieval. Understanding Media and Adapting to the User - 7th International Workshop, AMR 2009, Madrid, Spain, September 24-25, 2009, Revised Selected Papers, edited by Detyniecki M, García-Serrano A, Nürnberger A, 72-86.: Springer. doi: 10.1007/978-3-642-18449-9_7.
    • Wichterich M, Beecks C, Sundermeyer M, Seidl T. ‘Exploring multimedia databases via optimization-based relevance feedback and the earth mover's distance.’ In Proceedings of the 18th ACM Conference on Information and Knowledge Management, CIKM 2009, Hong Kong, China, November 2-6, 2009, edited by Cheung DW, Song I, Chu WW, Hu X, Lin JJ, 1621-1624.: ACM. doi: 10.1145/1645953.1646187.

    • Wichterich M, Beecks C, Seidl T. ‘Ranking multimedia databases via relevance feedback with history and foresight support.’ In Proceedings of the 24th International Conference on Data Engineering Workshops, ICDE 2008, April 7-12, 2008, Cancún, México, 596-599.: IEEE Computer Society. doi: 10.1109/ICDEW.2008.4498386.

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    • Berns F, Hüwel JD, Beecks C. LOGIC: Probabilistic Machine Learning for Time Series Classification. In 2021 IEEE International Conference on Data Mining (ICDM), 2021, doi: 10.1109/ICDM51629.2021.00113.
    • Hüwel J D, Berns F, Beecks C. ‘Automated Kernel Search for Gaussian Processes on Data Streams‘. In Proceedings of IEEE International Conference on Big Data, Orlando, FL, USA, 3584-3588, 2021, doi: 10.1109/BigData52589.2021.9671767.
    • Álvarez-Napagao S, Ashmore B, Barroso M, Barrué C, Beecks C, Berns F, Bosi I, Chala S, Ciulli N, Garcia-Gasulla M, Grass A, Ioannidis D, Jakubiak N, Köpke K, Lämsä V, Megias P, Nizamis A, Pastrone C, Rossini R, Sànchez-Marrè M, Ziliotti L.
      ‘knowlEdge Project - Concept, Methodology and Innovations for Artificial Intelligence in Industry 4.0‘. In Proceedings of the 19th IEEE International Conference on Industrial Informatics, Palma de Mallorca, Spain, 1-7, 2021, doi: 10.1109/INDIN45523.2021.9557410.
    • Berns F, Beecks C. ‘Complexity-Adaptive Gaussian Process Model Inference for Large-Scale Data.’ In Proceedings of the 2021 SIAM International Conference on Data Mining (SDM), 360-368, 2021, doi: 10.1137/1.9781611976700.41.
    • Berns F, Beecks C. ‘Stochastic Time Series Representation for Interval Pattern Mining via Gaussian Processes.’ In Proceedings of the 2021 SIAM International Conference on Data Mining (SDM), 10-18, 2021, doi: 10.1137/1.9781611976700.2.
    • Berns F, Strueber JH, Beecks C. ‘Local Gaussian Process Model Inference Classification for Time Series Data.’ In Proceedings of the 33rd International Conference on Scientific and Statistical Database Management, Tampa, Florida, USA. 2021, doi: 10.1145/3468791.3468839.

    • Berns F, Beecks C. ‘Automatic Gaussian Process Model Retrieval for Big Data.’ In Proceedings of the ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland, 2020. doi: 10.1145/3340531.3412182.
    • Berns F, Beecks C. ‘Towards Large-scale Gaussian Process Models for Efficient Bayesian Machine Learning.’ In Proceedings of the 9th International Conference on Data Science, Technology and Applications, 2020. doi: 10.5220/0009874702750282.
    • Berns F, Beecks C. ‘Large-scale Retrieval of Bayesian Machine Learning Models for Time Series Data via Gaussian Processes.’ In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 1: KDIR, 71-80: SciTePress, 2020. doi: 10.5220/0010109700710080.
    • Berns F, Schmidt K, Bracht I, Beecks C. ‘3CS Algorithm for Efficient Gaussian Process Model Retrieval.’ In Proceedings of the 25th International Conference on Pattern Recognition 2020, 1773-1780.: IEEE Computer Society. 2020, doi: 10.1109/ICPR48806.2021.9412805.
    • Berns F, Ramsdorf T, Beecks C. ‘Machine Learning for Storage Location Prediction in Industrial High Bay Warehouses.’ In 1st International Workshop on Industrial Machine Learning at 25th International Conference on Pattern Recognition 2020, 650-661.: Springer, 2020, doi: 10.1007/978-3-030-68799-1_47.
    • Berns F, Lange-Hegermann M, Beecks C. ‘Towards Gaussian Processes for Automatic and Interpretable Anomaly Detection in Industry 4.0.’ In Proceedings of the International Conference on Innovative Intelligent Industrial Production and Logistics - Volume 1: IN4PL,, 87-92.: SciTePress, 2020. doi: 10.5220/0010130300870092.
    • Pandian V P S, Suleri S, Beecks C, Jarke M. ‘MetaMorph: AI Assistance to Transform Lo-Fi Sketches to Higher Fidelities‘. In Proceedings 32nd Australian Conference on Human-Computer-Interaction 2020, Sydney, Australia, 403-412. doi: 10.1145/3441000.3441030.

    • Beecks C, Berns F, Schmidt KW. ‘Ptolemaic Indexing for Managing and Querying Internet of Things (IoT) Data.’ In 2019 IEEE International Conference on Big Data (Big Data), 4148-4151.: IEEE. doi: 10.1109/BigData47090.2019.9005725.
    • Beecks C, Schmidt KW, Berns F, Grass A. ‘Gaussian Processes for Anomaly Description in Production Environments.’ In Proceedings of the Workshops of the Joint Conference on Extending Database Technology and Database Theory, EDBT/ICDT 2019, Lisbon, Portugal, March 26, 2019.: CEUR-WS.org.
    • Berns F, Rossetto L, Schoeffmann K, Beecks C, Awad G. ‘V3C1 Dataset: An Evaluation of Content Characteristics.’ In Proceedings of the 2019 on International Conference on Multimedia Retrieval, ICMR 2019, Ottawa, ON, Canada, June 10-13, 2019, edited by El-Saddik A, Bimbo AD, Zhang Z, Hauptmann AG, Candan KS et al., 334-338.: ACM. doi: 10.1145/3323873.3325051.
    • Berns F, Schmidt K, Grass A, Beecks C. ‘A New Approach for Efficient Structure Discovery in IoT.’ In 2019 IEEE International Conference on Big Data (Big Data), 4152-4156.: IEEE. doi: 10.1109/BigData47090.2019.9006082.
    • Leibetseder A, Münzer B, Primus MJ, Kletz S, Schoeffmann K, Berns F, Beecks C. ‘lifeXplore at the Lifelog Search Challenge 2019.’ In Proceedings of the ACM Workshop on Lifelog Search Challenge, LSC@ICMR 2019, Ottawa, ON, Canada, 10 June 2019, edited by Gurrin C, Schöffmann K, Joho H, Dang-Nguyen D, Riegler M, Piras L, 13-17.: ACM. doi: 10.1145/3326460.3329157.
    • Sandfort F, Strieth-Kalthoff F, Kühnemund M, Beecks C, Glorius F. ‘A Structure-Based Platform for Predicting Chemical Reactivity.’ ChemRxiv 2019. doi: 10.26434/chemrxiv.9981488.v1.

    • Beecks C, Berrendorf M. ‘Optimal k-Nearest-Neighbor Query Processing via Multiple Lower Bound Approximations.’ In IEEE International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018, 614-623. doi: 10.1109/BigData.2018.8622493.
    • Beecks C, Devasya S, Schlutter R. ‘Machine Learning for Enhanced Waste Quantity Reduction: Insights from the MONSOON Industry 4.0 Project.’ In Selected papers from the International Conference on Machine Learning for Cyber Physical Systems, ML4CPS 2018, Karlsruhe, Germany, October 23-24, 1-6.: Springer, 2018. doi: 10.1007/978-3-662-58485-9\_1.
    • Beecks C, Grass A. ‘Efficient Point-Based Pattern Search in 3D Motion Capture Databases.’ In 6th IEEE International Conference on Future Internet of Things and Cloud, FiCloud 2018, Barcelona, Spain, August 6-8, 2018, edited by Younas M, Disso JP, 230-235.: IEEE Computer Society. doi: 10.1109/FiCloud.2018.00041.
    • Beecks C, Grass A, Devasya S. ‘Metric Indexing for Efficient Data Access in the Internet of Things.’ In IEEE International Conference on Big Data, Big Data 2018, Seattle, WA, USA, December 10-13, 2018, 5132-5136. doi: 10.1109/BigData.2018.8622387.
    • Grass A, Beecks C, Soto JAC. ‘Unsupervised Anomaly Detection in Production Lines.’ In Selected papers from the International Conference on Machine Learning for Cyber Physical Systems, ML4CPS 2018, Karlsruhe, Germany, October 23-24, 2018, 18-25.: Springer. doi: 10.1007/978-3-662-58485-9\_3.
    • Schoeffmann K, Husslein H, Kletz S, Petscharnig S, Münzer B, Beecks C. ‘Video retrieval in laparoscopic video recordings with dynamic content descriptors.’ Multimedia Tools Appl. 77, No. 13: 16813-16832, 2018. doi: 10.1007/s11042-017-5252-2.

    • Beecks C, Borutta F, Kröger P, Seidl T (Eds.): Similarity Search and Applications - 10th International Conference, SISAP 2017, Munich, Germany, October 4-6, 2017, Proceedings. : Springer. doi: 10.1007/978-3-319-68474-1.
    • Beecks C, Kletz S, Schoeffmann K. ‘Large-Scale Endoscopic Image and Video Linking with Gradient-Based Signatures.’ In Third IEEE International Conference on Multimedia Big Data, BigMM 2017, Laguna Hills, CA, USA, April 19-21, 2017, 17-21.: IEEE Computer Society. doi: 10.1109/BigMM.2017.44.
    • Münzer B, Primus MJ, Hudelist MA, Beecks C, Hürst W, Schoeffmann K. ‘When content-based video retrieval and human computation unite: Towards effective collaborative video search.’ In 2017 IEEE International Conference on Multimedia & Expo Workshops, ICME Workshops, Hong Kong, China, July 10-14, 2017, 214-219.: IEEE Computer Society. doi: 10.1109/ICMEW.2017.8026262.
    • Schüller D, Beecks C, Hassani M, Hinnell J, Brenger B, Seidl T, Mittelberg I. ‘Automated Pattern Analysis in Gesture Research: Similarity Measuring in 3D Motion Capture Models of Communicative Action.’ Digital Humanities Quarterly 11, No. 2, 2017.

    • Beecks C, Grass A. ‘Multi-step threshold algorithm for efficient feature-based query processing in large-scale multimedia databases.’ In 2016 IEEE International Conference on Big Data, BigData 2016, Washington DC, USA, December 5-8, 2016, edited by Joshi J, Karypis G, Liu L, Hu X, Ak R et al., 596-605.: IEEE. doi: 10.1109/BigData.2016.7840652.
    • Beecks C, Hassani M, Brenger B, Hinnell J, Schüller D, Mittelberg I, Seidl T. ‘Efficient Query Processing in 3D Motion Capture Gesture Databases.’ Int. J. Semantic Computing 10, No. 1: 5-26, 2016. doi: 10.1142/S1793351X16400018.
    • Beecks C, Uysal MS, Seidl T. ‘Distance-based Multimedia Indexing.’ In Proceedings of the 19th International Conference on Extending Database Technology, EDBT 2016, Bordeaux, France, March 15-16, 2016, Bordeaux, France, March 15-16, 2016., edited by Pitoura E, Maabout S, Koutrika G, Marian A, Tanca L, Manolescu I, Stefanidis K, 722-723.: OpenProceedings.org. doi: 10.5441/002/edbt.2016.105.
    • Hudelist MA, Beecks C, Schoeffmann K. ‘Finding the chameleon in your video collection.’ In Proceedings of the 7th International Conference on Multimedia Systems, MMSys 2016, Klagenfurt, Austria, May 10-13, 2016, edited by Timmerer C, 31:1-31:4.: ACM. doi: 10.1145/2910017.2910631.
    • Hudelist MA, Cobarzan C, Beecks C, Werken R, Kletz S, Hürst W, Schoeffmann K. ‘Collaborative Video Search Combining Video Retrieval with Human-Based Visual Inspection.’ In MultiMedia Modeling - 22nd International Conference, MMM 2016, Miami, FL, USA, January 4-6, 2016, Proceedings, Part II, edited by Tian Q, Sebe N, Qi G, Huet B, Hong R, Liu X, 400-405.: Springer. doi: 10.1007/978-3-319-27674-8_40.
    • Hürst W, Ching AIV, Hudelist MA, Primus MJ, Schoeffmann K, Beecks C. ‘A New Tool for Collaborative Video Search via Content-based Retrieval and Visual Inspection.’ In Proceedings of the 2016 ACM Conference on Multimedia Conference, MM 2016, Amsterdam, The Netherlands, October 15-19, 2016, edited by Hanjalic A, Snoek C, Worring M, Bulterman DCA, Huet B et al., 731-732.: ACM. doi: 10.1145/2964284.2973824.
    • Nies TD, Beecks C, Godin F, Neve WD, Stepien G et al. ‘Normalized Semantic Web Distance.’ In The Semantic Web. Latest Advances and New Domains - 13th International Conference, ESWC 2016, Heraklion, Crete, Greece, May 29 - June 2, 2016, Proceedings, edited by Sack H, Blomqvist E, d'Aquin M, Ghidini C, Ponzetto SP, Lange C, 69-84.: Springer. doi: 10.1007/978-3-319-34129-3_5.
    • Nies TD, Beecks C, Godin F, Neve WD, Stepien G et al. ‘A Distance-Based Approach for Semantic Dissimilarity in Knowledge Graphs.’ In Tenth IEEE International Conference on Semantic Computing, ICSC 2016, Laguna Hills, CA, USA, February 4-6, 2016, 254-257.: IEEE Computer Society. doi: 10.1109/ICSC.2016.55.
    • Schoeffmann K, Beecks C, Lux M, Uysal MS, Seidl T. ‘Content-based retrieval in videos from laparoscopic surgery.’ In Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, San Diego, California, United States, 27 February - 3 March 2016, edited by Webster RJ, Yaniv ZR, 97861V.: SPIE. doi: 10.1117/12.2216864.
    • Uysal MS, Beecks C, Sabinasz D, Schmücking J, Seidl T. ‘Efficient Query Processing using the Earth's Mover Distance in Video Databases.’ In Proceedings of the 19th International Conference on Extending Database Technology, EDBT 2016, Bordeaux, France, March 15-16, 2016, Bordeaux, France, March 15-16, 2016., edited by Pitoura E, Maabout S, Koutrika G, Marian A, Tanca L, Manolescu I, Stefanidis K, 389-400.: OpenProceedings.org. doi: 10.5441/002/edbt.2016.36.
    • Vocht LD, Beecks C, Verborgh R, Mannens E, Seidl T, Walle RV. ‘Effect of Heuristics on Serendipity in Path-Based Storytelling with Linked Data.’ In Human Interface and the Management of Information: Information, Design and Interaction - 18th International Conference, HCI International 2016 Toronto, Canada, July 17-22, 2016, Proceedings, Part I, edited by Yamamoto S, 238-251.: Springer. doi: 10.1007/978-3-319-40349-6_23.

    • Beecks C, Hassani M, Hinnell J, Schüller D, Brenger B, Mittelberg I, Seidl T. ‘Spatiotemporal Similarity Search in 3D Motion Capture Gesture Streams.’ In Advances in Spatial and Temporal Databases - 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings, edited by Claramunt C, Schneider M, Wong RC, Xiong L, Loh W, Shahabi C, Li K, 355-372.: Springer. doi: 10.1007/978-3-319-22363-6_19.
    • Beecks C, Hassani M, Obeloer F, Seidl T. ‘Efficient Query Processing in 3D Motion Capture Databases via Lower Bound Approximation of the Gesture Matching Distance.’ In 2015 IEEE International Symposium on Multimedia, ISM 2015, Miami, FL, USA, December 14-16, 2015, 148-153.: IEEE Computer Society. doi: 10.1109/ISM.2015.86.
    • Beecks C, Hassani M, Obeloer F, Seidl T. ‘Efficient Distance-Based Gestural Pattern Mining in Spatiotemporal 3D Motion Capture Databases.’ In IEEE International Conference on Data Mining Workshop, ICDMW 2015, Atlantic City, NJ, USA, November 14-17, 2015, 1425-1432.: IEEE Computer Society. doi: 10.1109/ICDMW.2015.194.
    • Beecks C, Schoeffmann K, Lux M, Uysal MS, Seidl T. ‘Endoscopic Video Retrieval: A Signature-Based Approach for Linking Endoscopic Images with Video Segments.’ In 2015 IEEE International Symposium on Multimedia, ISM 2015, Miami, FL, USA, December 14-16, 2015, 33-38.: IEEE Computer Society. doi: 10.1109/ISM.2015.21.
    • Beecks C, Uysal MS, Hermanns J, Seidl T. ‘Gradient-based Signatures for Efficient Similarity Search in Large-scale Multimedia Databases.’ In Proceedings of the 24th ACM International Conference on Information and Knowledge Management, CIKM 2015, Melbourne, VIC, Australia, October 19 - 23, 2015, edited by Bailey J, Moffat A, Aggarwal CC, Rijke M, Kumar R et al., 1241-1250.: ACM. doi: 10.1145/2806416.2806459.
    • Beecks C, Uysal MS, Seidl T. ‘Content-Based Image Retrieval with Gaussian Mixture Models.’ In MultiMedia Modeling - 21st International Conference, MMM 2015, Sydney, NSW, Australia, January 5-7, 2015, Proceedings, Part I, edited by He X, Luo S, Tao D, Xu C, Yang J, Hasan MA, 294-305.: Springer. doi: 10.1007/978-3-319-14445-0_26.
    • Beecks C, Uysal MS, Seidl T. ‘Gradient-based signatures for big multimedia data.’ In 2015 IEEE International Conference on Big Data, Big Data 2015, Santa Clara, CA, USA, October 29 - November 1, 2015, 2834-2835.: IEEE. doi: 10.1109/BigData.2015.7364093.
    • Beecks C, Uysal MS, Seidl T. ‘Distance-based Multimedia Indexing.’ In Datenbanksysteme für Business, Technologie und Web (BTW 2015) - Workshopband, 2.-3. März 2015, Hamburg, Germany, edited by Ritter N, Henrich A, Lehner W, Thor A, Friedrich S, Wingerath W, 265-268.: GI.
    • Beecks C, Uysal MS, Seidl T. ‘Earth Mover's Distance vs. Quadratic form Distance: An Analytical and Empirical Comparison.’ In 2015 IEEE International Symposium on Multimedia, ISM 2015, Miami, FL, USA, December 14-16, 2015, 233-236.: IEEE Computer Society. doi: 10.1109/ISM.2015.76.
    • Hassani M, Beecks C, Töws D, Seidl T. ‘Mining Sequential Patterns of Event Streams in a Smart Home Application.’ In Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB, Trier, Germany, October 7-9, 2015., edited by Bergmann R, Görg S, Müller G, 159-170.: CEUR-WS.org.
    • Hassani M, Beecks C, Töws D, Serbina T, Haberstroh M et al. ‘Sequential Pattern Mining of Multimodal Streams in the Humanities.’ In Datenbanksysteme für Business, Technologie und Web (BTW), 16. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS), 4.-6.3.2015 in Hamburg, Germany. Proceedings, edited by Seidl T, Ritter N, Schöning H, Sattler K, Härder T, Friedrich S, Wingerath W, 683-686.: GI.
    • Töws D, Hassani M, Beecks C, Seidl T. ‘Optimizing Sequential Pattern Mining Within Multiple Streams.’ In Datenbanksysteme für Business, Technologie und Web (BTW 2015) - Workshopband, 2.-3. März 2015, Hamburg, Germany, edited by Ritter N, Henrich A, Lehner W, Thor A, Friedrich S, Wingerath W, 223-232.: GI.
    • Uysal MS, Beecks C, Sabinasz D, Seidl T. ‘Large-scale Efficient and Effective Video Similarity Search.’ In Proceedings of the 2015 Workshop on Large-Scale and Distributed System for Information Retrieval, LSDS-IR 2015, Melbourne, Australia, October 23, 2015, edited by Altingovde IS, Cambazoglu BB, Tonellotto N, 3-8.: ACM. doi: 10.1145/2809948.2809950.
    • Uysal MS, Beecks C, Sabinasz D, Seidl T. ‘Effective Content-Based Near-Duplicate Video Detection.’ In 2015 IEEE International Symposium on Multimedia, ISM 2015, Miami, FL, USA, December 14-16, 2015, 254-257.: IEEE Computer Society. doi: 10.1109/ISM.2015.60.
    • Uysal MS, Beecks C, Sabinasz D, Seidl T. ‘FELICITY: A Flexible Video Similarity Search Framework Using the Earth Mover's Distance.’ In Similarity Search and Applications - 8th International Conference, SISAP 2015, Glasgow, UK, October 12-14, 2015, Proceedings, edited by Amato G, Connor RCH, Falchi F, Gennaro C, 347-350.: Springer. doi: 10.1007/978-3-319-25087-8_34.
    • Uysal MS, Beecks C, Schmücking J, Seidl T. ‘Efficient similarity search in scientific databases with feature signatures.’ In Proceedings of the 27th International Conference on Scientific and Statistical Database Management, SSDBM '15, La Jolla, CA, USA, June 29 - July 1, 2015, edited by Gupta A, Rathbun SL, 30:1-30:12.: ACM. doi: 10.1145/2791347.2791384.
    • Uysal MS, Beecks C, Seidl T. ‘On efficient content-based near-duplicate video detection.’ In 13th International Workshop on Content-Based Multimedia Indexing, CBMI 2015, Prague, Czech Republic, June 10-12, 2015, 1-6.: IEEE. doi: 10.1109/CBMI.2015.7153633.
    • Vocht LD, Beecks C, Verborgh R, Seidl T, Mannens E, Walle RV. ‘Improving Semantic Relatedness in Paths for Storytelling with Linked Data on the Web.’ In The Semantic Web: ESWC 2015 Satellite Events - ESWC 2015 Satellite Events Portorož, Slovenia, May 31 - June 4, 2015, Revised Selected Papers, edited by Gandon F, Guéret C, Villata S, Breslin JG, Faron-Zucker C, Zimmermann A, 31-35.: Springer. doi: 10.1007/978-3-319-25639-9_6.

    • Beecks C, Kirchhoff S, Seidl T. ‘On the Stability of Signature-Based Distance Functions for Content-Based Image Retrieval.’ In Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014., edited by Seidl T, Hassani M, Beecks C, 226.: CEUR-WS.org.
    • Beecks C, Kirchhoff S, Seidl T. ‘On stability of signature-based similarity measures for content-based image retrieval.’ Multimedia Tools Appl. 71, No. 1: 349-362, 2014. doi: 10.1007/s11042-012-1334-3.
    • Godin F, Nies TD, Beecks C, Vocht LD, Neve WD et al. ‘The Normalized Freebase Distance.’ In The Semantic Web: ESWC 2014 Satellite Events - ESWC 2014 Satellite Events, Anissaras, Crete, Greece, May 25-29, 2014, Revised Selected Papers, edited by Presutti V, Blomqvist E, Troncy R, Sack H, Papadakis I, Tordai A, 218-221.: Springer. doi: 10.1007/978-3-319-11955-7_22.
    • Nies TD, Beecks C, Neve WD, Seidl T, Mannens E, Walle RV. ‘Towards Named-Entity-based Similarity Measures: Challenges and Opportunities.’ In Proceedings of the 7th International Workshop on Exploiting Semantic Annotations in Information Retrieval, ESAIR '14, Shanghai, China, November 7, 2014, edited by Alonso O, Kamps J, Karlgren J, 9-11.: ACM. doi: 10.1145/2663712.2666194.
    • Seidl T, Hassani M, Beecks C (Eds.): Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014. : CEUR-WS.org.
    • Uysal MS, Beecks C, Schmücking J, Seidl T. ‘Efficient Filter Approximation Using the Earth Mover's Distance in Very Large Multimedia Databases with Feature Signatures.’ In Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management, CIKM 2014, Shanghai, China, November 3-7, 2014, edited by Li J, Wang XS, Garofalakis MN, Soboroff I, Suel T, Wang M, 979-988.: ACM. doi: 10.1145/2661829.2661877.
    • Uysal MS, Beecks C, Seidl T. ‘On Efficient Query Processing with the Earth Mover's Distance.’ In Proceedings of the 7th Workshop on Ph.D Students, PIKM@CIKM 2014, Shanghai, China, November 3, 2014, edited by Melo G, Kacimi M, Varde AS, 25-32.: ACM. doi: 10.1145/2663714.2668047.

    • Beecks C. Distance based similarity models for content based multimedia retrieval Doctoral Thesis, 2013, RWTH Aachen University.
    • Beecks C, Kirchhoff S, Seidl T. ‘Signature matching distance for content-based image retrieval.’ In International Conference on Multimedia Retrieval, ICMR'13, Dallas, TX, USA, April 16-19, 2013, edited by Jain R, Prabhakaran B, Worring M, Smith JR, Chua T, 41-48.: ACM. doi: 10.1145/2461466.2461474.
    • Beecks C, Uysal MS, Driessen P, Seidl T. ‘Content-based exploration of multimedia databases.’ In 11th International Workshop on Content-Based Multimedia Indexing, CBMI 2013, Veszprém, Hungary, June 17-19, 2013, 59-64.: IEEE. doi: 10.1109/CBMI.2013.6576553.
    • Hetland ML, Skopal T, Lokoc J, Beecks C. ‘Ptolemaic access methods: Challenging the reign of the metric space model.’ Inf. Syst. 38, 2013, No. 7: 989-1006. doi: 10.1016/j.is.2012.05.011.

    • Beecks C, Seidl T. ‘On Stability of Adaptive Similarity Measures for Content-Based Image Retrieval.’ In Advances in Multimedia Modeling - 18th International Conference, MMM 2012, Klagenfurt, Austria, January 4-6, 2012. Proceedings, edited by Schoeffmann K, Mérialdo B, Hauptmann AG, Ngo C, Andreopoulos Y, Breiteneder C, 346-357.: Springer. doi: 10.1007/978-3-642-27355-1_33.
    • Ivanescu AM, Wichterich M, Beecks C, Seidl T. ‘The ClasSi coefficient for the evaluation of ranking quality in the presence of class similarities.’ Frontiers Comput. Sci. 6, 2012, No. 5: 568-580. doi: 10.1007/s11704-012-1175-2.
    • Krulis M, Skopal T, Lokoc J, Beecks C. ‘Combining CPU and GPU architectures for fast similarity search.’ Distributed and Parallel Databases 30, 2012, No. 3-4: 179-207. doi: 10.1007/s10619-012-7092-4.

    • Beecks C, Assent I, Seidl T. ‘Content-Based Multimedia Retrieval in the Presence of Unknown User Preferences.’ In Advances in Multimedia Modeling - 17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part I, edited by Lee K, Tsai W, Liao HM, Chen T, Hsieh J, Tseng C, 140-150.: Springer. doi: 10.1007/978-3-642-17832-0_14.
    • Beecks C, Ivanescu AM, Kirchhoff S, Seidl T. ‘Modeling image similarity by Gaussian mixture models and the Signature Quadratic Form Distance.’ In IEEE International Conference on Computer Vision, ICCV 2011, Barcelona, Spain, November 6-13, 2011, edited by Metaxas DN, Quan L, Sanfeliu A, Gool LJV, 1754-1761.: IEEE Computer Society. doi: 10.1109/ICCV.2011.6126440.
    • Beecks C, Ivanescu AM, Kirchhoff S, Seidl T. ‘Modeling multimedia contents through probabilistic feature signatures.’ In Proceedings of the 19th International Conference on Multimedia 2011, Scottsdale, AZ, USA, November 28 - December 1, 2011, edited by Candan KS, Panchanathan S, Prabhakaran B, Sundaram H, Feng W, Sebe N, 1433-1436.: ACM. doi: 10.1145/2072298.2072033.
    • Beecks C, Ivanescu AM, Seidl T, Martin D, Pischke P, Kneer R. ‘Applying similarity search for the investigation of the fuel injection process.’ In Fourth International Conference on Similarity Search and Applications, SISAP 2011, Lipari Island, Italy, June 30 - July 01, 2011, edited by Ferro A, 117-118.: ACM. doi: 10.1145/1995412.1995436.
    • Beecks C, Lokoc J, Seidl T, Skopal T. ‘Indexing the signature quadratic form distance for efficient content-based multimedia retrieval.’ In Proceedings of the 1st International Conference on Multimedia Retrieval, ICMR 2011, Trento, Italy, April 18 - 20, 2011, edited by Natale FGBD, Bimbo AD, Hanjalic A, Manjunath BS, Satoh S, 24.: ACM. doi: 10.1145/1991996.1992020.
    • Beecks C, Seidl T. ‘Analyzing the inner workings of the Signature Quadratic Form Distance.’ In Proceedings of the 2011 IEEE International Conference on Multimedia and Expo, ICME 2011, 11-15 July, 2011, Barcelona, Catalonia, Spain, 1-6.: IEEE Computer Society. doi: 10.1109/ICME.2011.6012243.
    • Beecks C, Uysal MS, Seidl T. ‘L2-Signature Quadratic Form Distance for Efficient Query Processing in Very Large Multimedia Databases.’ In Advances in Multimedia Modeling - 17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011, Proceedings, Part I, edited by Lee K, Tsai W, Liao HM, Chen T, Hsieh J, Tseng C, 381-391.: Springer. doi: 10.1007/978-3-642-17832-0_36.
    • Krulis M, Lokoc J, Beecks C, Skopal T, Seidl T. ‘Processing the signature quadratic form distance on many-core GPU architectures.’ In Proceedings of the 20th ACM Conference on Information and Knowledge Management, CIKM 2011, Glasgow, United Kingdom, October 24-28, 2011, edited by Macdonald C, Ounis I, Ruthven I, 2373-2376.: ACM. doi: 10.1145/2063576.2063970.
    • Lokoc J, Beecks C, Seidl T, Skopal T. ‘Parameterized earth mover's distance for efficient metric space indexing.’ In Fourth International Conference on Similarity Search and Applications, SISAP 2011, Lipari Island, Italy, June 30 - July 01, 2011, edited by Ferro A, 121-122.: ACM. doi: 10.1145/1995412.1995438.
    • Lokoc J, Hetland ML, Skopal T, Beecks C. ‘Ptolemaic indexing of the signature quadratic form distance.’ In Fourth International Conference on Similarity Search and Applications, SISAP 2011, Lipari Island, Italy, June 30 - July 01, 2011, edited by Ferro A, 9-16.: ACM. doi: 10.1145/1995412.1995417.
    • Schoeffmann K, Ahlströ}m D, Beecks C. ‘3D Image Browsing on Mobile Devices.’ In 2011 IEEE International Symposium on Multimedia, ISM 2011, Dana Point, CA, USA, December 5-7, 2011, 335-336.: IEEE Computer Society. doi: 10.1109/ISM.2011.60.

    • Beecks C, Driessen P, Seidl T. ‘Index support for content-based multimedia exploration.’ In Proceedings of the 18th International Conference on Multimedia 2010, Firenze, Italy, October 25-29, 2010, edited by Bimbo AD, Chang S, Smeulders AWM, 999-1002.: ACM. doi: 10.1145/1873951.1874134.
    • Beecks C, Stadelmann T, Freisleben B, Seidl T. ‘Visual speaker model exploration.’ In Proceedings of the 2010 IEEE International Conference on Multimedia and Expo, ICME 2010, 19-23 July 2010, Singapore, 727-728.: IEEE Computer Society. doi: 10.1109/ICME.2010.5583176.
    • Beecks C, Uysal MS, Seidl T. ‘Similarity matrix compression for efficient signature quadratic form distance computation.’ In Third International Workshop on Similarity Search and Applications, SISAP 2010, 18-19 September 2010, Istanbul, Turkey, edited by Ciaccia P, Patella M, 109-114.: ACM. doi: 10.1145/1862344.1862361.
    • Beecks C, Uysal MS, Seidl T. ‘Signature Quadratic Form Distance.’ In Proceedings of the 9th ACM International Conference on Image and Video Retrieval, CIVR 2010, Xi'an, China, July 5-7, 2010, edited by Li S, Gao X, Sebe N, 438-445.: ACM. doi: 10.1145/1816041.1816105.
    • Beecks C, Uysal MS, Seidl T. ‘A comparative study of similarity measures for content-based multimedia retrieval.’ In Proceedings of the 2010 IEEE International Conference on Multimedia and Expo, ICME 2010, 19-23 July 2010, Singapore, 1552-1557.: IEEE Computer Society. doi: 10.1109/ICME.2010.5582949.
    • Beecks C, Uysal MS, Seidl T. ‘Efficient k-nearest neighbor queries with the Signature Quadratic Form Distance.’ In Workshops Proceedings of the 26th International Conference on Data Engineering, ICDE 2010, March 1-6, 2010, Long Beach, California, USA, 10-15.: IEEE Computer Society. doi: 10.1109/ICDEW.2010.5452772.
    • Beecks C, Wiedenfeld S, Seidl T. ‘Improving the Efficiency of Content-Based Multimedia Exploration.’ In 20th International Conference on Pattern Recognition, ICPR 2010, Istanbul, Turkey, 23-26 August 2010, 3163-3166.: IEEE Computer Society. doi: 10.1109/ICPR.2010.774.

    • Beecks C, Uysal MS, Seidl T. ‘Signature quadratic form distances for content-based similarity.’ In Proceedings of the 17th International Conference on Multimedia 2009, Vancouver, British Columbia, Canada, October 19-24, 2009, edited by Gao W, Rui Y, Hanjalic A, Xu C, Steinbach EG, El-Saddik A, Zhou MX, 697-700.: ACM. doi: 10.1145/1631272.1631391.
    • Beecks C, Wichterich M, Seidl T. „Metrische Anpassung der Earth Mover's Distanz zur Ähnlichkeitssuche in Multimedia-Datenbanken.“ In Datenbanksysteme in Business, Technologie und Web (BTW 2009), 13. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS), Proceedings, 2.-6. März 2009, Münster, Germany, herausgegeben von Freytag JC, Ruf T, Lehner W, Vossen G, 207-216.: GI.
    • Wichterich M, Beecks C, Sundermeyer M, Seidl T. ‘Relevance Feedback for the Earth Mover's Distance.’ In Adaptive Multimedia Retrieval. Understanding Media and Adapting to the User - 7th International Workshop, AMR 2009, Madrid, Spain, September 24-25, 2009, Revised Selected Papers, edited by Detyniecki M, García-Serrano A, Nürnberger A, 72-86.: Springer. doi: 10.1007/978-3-642-18449-9_7.
    • Wichterich M, Beecks C, Sundermeyer M, Seidl T. ‘Exploring multimedia databases via optimization-based relevance feedback and the earth mover's distance.’ In Proceedings of the 18th ACM Conference on Information and Knowledge Management, CIKM 2009, Hong Kong, China, November 2-6, 2009, edited by Cheung DW, Song I, Chu WW, Hu X, Lin JJ, 1621-1624.: ACM. doi: 10.1145/1645953.1646187.

    • Wichterich M, Beecks C, Seidl T. ‘Ranking multimedia databases via relevance feedback with history and foresight support.’ In Proceedings of the 24th International Conference on Data Engineering Workshops, ICDE 2008, April 7-12, 2008, Cancún, México, 596-599.: IEEE Computer Society. doi: 10.1109/ICDEW.2008.4498386.
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