Professor Dr. Christian Beecks

Professor Dr. Christian Beecks

Einsteinstraße 62, Raum 203
48149 Münster

T: +49 251 83-33804
F: +49 251 83-33755

  • Forschungsschwerpunkte

    • Data Science
    • Data Engineering
    • Big Data
    • Machine Learning
    • Multimedia Databases

  • Vita

    Akademische Ausbildung

    Promotion in Informatik, RWTH Aachen, Deutschland. Thema der Dissertation: Distance-based Similarity Models for Content-based Multimedia Retrieval.
    Diplom in Informatik, RWTH Aachen, Deutschland. Thema der Diplomarbeit: Relevance Feedback für EMD-basierte Ähnlichkeitssuche.

    Beruflicher Werdegang

    Forschungsgruppenleiter, Data Science und Künstliche Intelligenz, Fraunhofer-Institut für Angewandte Informationstechnik FIT, Deutschland.
    Professor für Praktische Informatik, Universität Münster, Deutschland.
    Senior Researcher, User-Centered Ubiquitous Computing, Fraunhofer-Institut für Angewandte Informationstechnik FIT, Deutschland.
    Akademischer Rat, RWTH Aachen, Deutschland.
    Postdoktorand, RWTH Aachen, Deutschland.
    Doktorand und wissenschaftlicher Mitarbeiter, RWTH Aachen, Deutschland.

    Preise

    Best Research Paper Award – Society for Industrial and Applied Mathematics (SIAM)
    Best Poster Award – Committee of the Workshop Gesture & Technology
    Best Paper Award: "Automated Pattern Analysis in Gesture Research: Similarity Measuring in 3D Motion Capture Models of Communicative Action" – Göttingen Dialog in Digital Humanities
    Best Paper Award: "Ptolemaic Indexing of the Signature Quadratic Form Distance" – International Conference on Similarity Search and Applications

  • Projekte

    • GAIA – Standortübergreifendes Graduiertenkolleg: „Trustworthy AI for Seamless Problem solving: Next generation Intelligence Joins Robust Data Analysis“ (Data NInJA) - Promotionsthema: "Gaußprozesse für automatische und interpretierbare Anomalie-Erkennung" ( – )
      participations in other joint project: MKW - Förderlinie „Künstliche Intelligenz/Maschinelles Lernen“ - Standortübergreifendes Graduiertenkolleg | Förderkennzeichen: 005-2010-0003
    • knowlEdge – Towards AI powered manufacturing services, processes, and products in an edge-to-cloud-knowlEdge continuum for humans [in-the-loop] ( – )
      EU-Projekt koordiniert außerhalb der Universität Münster: EU H2020 - Research and innovation actions | Förderkennzeichen: 957331
    • Applied IoT Data Analytics (seit )
      Eigenmittelprojekt
    • Medical Video Analysis ( – )
      Eigenmittelprojekt
    • Gesture Analytics ( – )
      Eigenmittelprojekt
    • Video Search and Retrieval ( – )
      Eigenmittelprojekt
    • Query Processing (seit )
      Eigenmittelprojekt
    • Semantic Data Access ( – )
      Eigenmittelprojekt
    • Metric and Ptolemaic Access Methods (seit )
      Eigenmittelprojekt
    • Performance Studies ( – )
      Eigenmittelprojekt
    • Sequential Pattern Mining ( – )
      Eigenmittelprojekt
    • Similarity Search (seit )
      Eigenmittelprojekt
    • Signature Quadratic Form Distance ( – )
      Eigenmittelprojekt
    • Multimedia Data Exploration ( – )
      Eigenmittelprojekt

  • Publikationen

    • Berns F, Strueber JH, Beecks C. . ‘Local Gaussian Process Model Inference Classification for Time Series Data.’ Contributed to the 33rd International Conference on Scientific and Statistical Database Management, Tampa, Florida, USA. doi: 10.1145/3468791.3468839.
    • 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. doi: 10.1137/1.9781611976700.2.
    • 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. doi: 10.1137/1.9781611976700.41.
    • 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. Heidelberg: Springer. doi: 10.1007/978-3-030-68799-1_47.
    • Berns F, Schmidt K, Bracht I, Beecks C. . ‘3CS Algorithm for Efficient Gaussian Process Model Retrieval.’ In Proceedings 25th of the International Conference on Pattern Recognition 2020, 1773–1780. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/ICPR48806.2021.9412805.
    • 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. Setúbal: SciTePress. doi: 10.5220/0010109700710080.
    • 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. Setúbal: SciTePress. doi: 10.5220/0010130300870092.
    • Berns F, Beecks C. . ‘Automatic Gaussian Process Model Retrieval for Big Data.’ Contributed to the ACM International Conference on Information and Knowledge Management, Virtual Event, Ireland. 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. doi: 10.5220/0009874702750282.
    • 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. New York City: Wiley-IEEE Press. doi: 10.1109/BigData47090.2019.9006082.
    • 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. New York City: Wiley-IEEE Press. doi: 10.1109/BigData47090.2019.9005725.
    • 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.
    • 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, Bertini M, Xie L, Wei X, 334–338. New York, NY: ACM Press. doi: 10.1145/3323873.3325051.
    • 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. New York, NY: ACM Press. doi: 10.1145/3326460.3329157.
    • 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. Aachen: CEUR-WS.
    • 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. Heidelberg: Springer. doi: 10.1007/978-3-662-58485-9\_3.
    • 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, 2018, 1–6. Heidelberg: Springer. doi: 10.1007/978-3-662-58485-9\_1.
    • 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.
    • 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, 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. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/FiCloud.2018.00041.
    • 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, Nr. 13: 16813–16832. 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. Düsseldorf: Springer VDI Verlag. doi: 10.1007/978-3-319-68474-1.
    • 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. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/ICMEW.2017.8026262.
    • 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. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/BigMM.2017.44.
    • 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, Nr. 2.
    • Nies TD, Beecks C, Godin F, Neve WD, Stepien G, Arndt D, Vocht LD, Verborgh R, Seidl T, Mannens E, Walle RV. . ‘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. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/ICSC.2016.55.
    • 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. New York, NY: ACM Press. 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. Heidelberg: 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, Kelliher A, Kompatsiaris Y, Li J, 731–732. New York, NY: ACM Press. doi: 10.1145/2964284.2973824.
    • 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. Bellingham, WA: SPIE. doi: 10.1117/12.2216864.
    • 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. Heidelberg: Springer. doi: 10.1007/978-3-319-40349-6_23.
    • Nies TD, Beecks C, Godin F, Neve WD, Stepien G, Arndt D, Vocht LD, Verborgh R, Seidl T, Mannens E, Walle RV. . ‘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. Heidelberg: Springer. doi: 10.1007/978-3-319-34129-3_5.
    • 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. N/A: Selbstverlag / Eigenverlag. doi: 10.5441/002/edbt.2016.105.
    • 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. N/A: Selbstverlag / Eigenverlag. doi: 10.5441/002/edbt.2016.36.
    • 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, Xia Y, Xu W, Sato A, Rachuri S, Ungar LH, Yu PS, Govindaraju R, Suzumura T, 596–605. New York City: Wiley-IEEE Press. 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, Nr. 1: 5–26. doi: 10.1142/S1793351X16400018.
    • 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. New York, NY: ACM Press. doi: 10.1145/2791347.2791384.
    • 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. Heidelberg: Springer. doi: 10.1007/978-3-319-22363-6_19.
    • 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. Heidelberg: Springer. doi: 10.1007/978-3-319-25087-8_34.
    • 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. Heidelberg: Springer. doi: 10.1007/978-3-319-14445-0_26.
    • 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. Aachen: CEUR-WS.
    • 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. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/ISM.2015.60.
    • 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. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/ISM.2015.76.
    • 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. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/ISM.2015.86.
    • 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. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/ISM.2015.21.
    • 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. New York City: Wiley-IEEE Computer Society Press. doi: 10.1109/ICDMW.2015.194.
    • 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. Heidelberg: Springer. doi: 10.1007/978-3-319-25639-9_6.
    • 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, Murdock V, Sellis TK, Yu JX, 1241–1250. New York, NY: ACM Press. doi: 10.1145/2806416.2806459.
    • 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. New York, NY: ACM Press. doi: 10.1145/2809948.2809950.
    • 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. New York City: Wiley-IEEE Press. doi: 10.1109/CBMI.2015.7153633.
    • Hassani M, Beecks C, Töws D, Serbina T, Haberstroh M, Niemietz P, Jeschke S, Neumann S, Seidl T. . ‘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. Bonn: Gesellschaft für Informatik.
    • 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. Bonn: Gesellschaft für Informatik.
    • 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. Bonn: Gesellschaft für Informatik.
    • 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. New York City: Wiley-IEEE Press. doi: 10.1109/BigData.2015.7364093.
    • Seidl T, Hassani M, Beecks C (Eds.): . Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, Aachen, Germany, September 8-10, 2014. Aachen: CEUR-WS.
    • 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. Aachen: CEUR-WS.
    • Godin F, Nies TD, Beecks C, Vocht LD, Neve WD, Mannens E, Seidl T, Walle RV. . ‘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. Heidelberg: Springer. doi: 10.1007/978-3-319-11955-7_22.
    • 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. New York, NY: ACM Press. 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. New York, NY: ACM Press. doi: 10.1145/2663714.2668047.
    • 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. New York, NY: ACM Press. doi: 10.1145/2663712.2666194.
    • Beecks C, Kirchhoff S, Seidl T. . ‘On stability of signature-based similarity measures for content-based image retrieval.’ Multimedia Tools Appl. 71, Nr. 1: 349–362. doi: 10.1007/s11042-012-1334-3.
    • 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. New York, NY: ACM Press. 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. New York City: Wiley-IEEE Press. 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, Nr. 7: 989–1006. doi: 10.1016/j.is.2012.05.011.
    • Beecks C. . Distance based similarity models for content based multimedia retrieval Dissertationsschrift, RWTH Aachen University.
    • 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. Heidelberg: 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, Nr. 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, Nr. 3-4: 179–207. doi: 10.1007/s10619-012-7092-4.
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