1. //
  2. Start
  3. //
  4. Publications
  5. Finding Similar Movements in Positional ...
  6. Output formats
  7. //

Finding Similar Movements in Positional Data Streams

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Standard

Finding Similar Movements in Positional Data Streams. / Haase, Jens; Brefeld, Ulf.
Machine Learning and Data Mining for Sports Analytics - MLSA 2013: Proceedings. ed. / Davis Jesse; Jan Van Haaren; Albrecht Zimmermann. Prag: Sun Site Central Europe (RWTH Aachen University), 2013. p. 49-57 (CEUR Workshop Proceedings; No. 1969).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Harvard

Haase, J & Brefeld, U 2013, Finding Similar Movements in Positional Data Streams. in D Jesse, J Van Haaren & A Zimmermann (eds), Machine Learning and Data Mining for Sports Analytics - MLSA 2013: Proceedings. CEUR Workshop Proceedings, no. 1969, Sun Site Central Europe (RWTH Aachen University), Prag, pp. 49-57, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECMLPKDD 2013, Prag, Czech Republic, 23.09.13. <http://www.ecmlpkdd2013.org/wp-content/uploads/2013/09/mlsa13_submission_13.pdf>

APA

Haase, J., & Brefeld, U. (2013). Finding Similar Movements in Positional Data Streams. In D. Jesse, J. Van Haaren, & A. Zimmermann (Eds.), Machine Learning and Data Mining for Sports Analytics - MLSA 2013: Proceedings (pp. 49-57). (CEUR Workshop Proceedings; No. 1969). Sun Site Central Europe (RWTH Aachen University). http://www.ecmlpkdd2013.org/wp-content/uploads/2013/09/mlsa13_submission_13.pdf

Vancouver

Haase J, Brefeld U. Finding Similar Movements in Positional Data Streams. In Jesse D, Van Haaren J, Zimmermann A, editors, Machine Learning and Data Mining for Sports Analytics - MLSA 2013: Proceedings. Prag: Sun Site Central Europe (RWTH Aachen University). 2013. p. 49-57. (CEUR Workshop Proceedings; 1969).

Bibtex

@inbook{f3b5a32bf1784fb39a85a24c95211d75,
title = "Finding Similar Movements in Positional Data Streams",
abstract = "In this paper, we study the problem of efficiently finding similar movements in positional data streams, given a query trajectory. Our approach is based on a translation-, rotation-, and scale-invariant representation of movements. Near-neighbours given a query trajectory are then efficiently computed using dynamic time warping and locality sensitive hashing. Empirically, we show the efficiency and accuracy of our approach on positional data streams recorded from a real soccer game.",
keywords = "Informatics, Business informatics",
author = "Jens Haase and Ulf Brefeld",
year = "2013",
language = "English",
series = "CEUR Workshop Proceedings",
publisher = "Sun Site Central Europe (RWTH Aachen University)",
number = "1969",
pages = "49--57",
editor = "Davis Jesse and {Van Haaren}, Jan and Albrecht Zimmermann",
booktitle = "Machine Learning and Data Mining for Sports Analytics - MLSA 2013",
address = "Germany",
note = "European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECMLPKDD 2013, ECMLPKDD 2013 ; Conference date: 23-09-2013 Through 27-09-2013",
url = "http://www.ecmlpkdd2013.org/",

}

RIS

TY - CHAP

T1 - Finding Similar Movements in Positional Data Streams

AU - Haase, Jens

AU - Brefeld, Ulf

PY - 2013

Y1 - 2013

N2 - In this paper, we study the problem of efficiently finding similar movements in positional data streams, given a query trajectory. Our approach is based on a translation-, rotation-, and scale-invariant representation of movements. Near-neighbours given a query trajectory are then efficiently computed using dynamic time warping and locality sensitive hashing. Empirically, we show the efficiency and accuracy of our approach on positional data streams recorded from a real soccer game.

AB - In this paper, we study the problem of efficiently finding similar movements in positional data streams, given a query trajectory. Our approach is based on a translation-, rotation-, and scale-invariant representation of movements. Near-neighbours given a query trajectory are then efficiently computed using dynamic time warping and locality sensitive hashing. Empirically, we show the efficiency and accuracy of our approach on positional data streams recorded from a real soccer game.

KW - Informatics

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=85007206303&partnerID=8YFLogxK

M3 - Article in conference proceedings

T3 - CEUR Workshop Proceedings

SP - 49

EP - 57

BT - Machine Learning and Data Mining for Sports Analytics - MLSA 2013

A2 - Jesse, Davis

A2 - Van Haaren, Jan

A2 - Zimmermann, Albrecht

PB - Sun Site Central Europe (RWTH Aachen University)

CY - Prag

T2 - European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases - ECMLPKDD 2013

Y2 - 23 September 2013 through 27 September 2013

ER -

Other publications by the same author(s)

Interactive sequential generative models for team sports

Fassmeyer, D., Cordes, M. & Brefeld, U., 02.2025, In: Machine Learning. 114, 2, 15 p., 38.

Research output: Journal contributions › Journal articles › Research › peer-review

Joint Item Response Models for Manual and Automatic Scores on Open-Ended Test Items

Bengs, D., Brefeld, U., Kroehne, U. & Zehner, F., 2025, (Accepted/In press) In: Psychometrika.

Research output: Journal contributions › Journal articles › Research › peer-review

Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers

Brefeld, U. (Editor), Davis, J. (Editor), Van Haaren, J. (Editor) & Zimmermann, A. (Editor), 2025, Cham: Springer Verlag. 119 p. (Communications in Computer and Information Science; vol. 2460)

Research output: Books and anthologies › Conference proceedings › Research

Masked autoencoder for multiagent trajectories

Rudolph, Y. & Brefeld, U., 02.2025, In: Machine Learning. 114, 2, 18 p., 44.

Research output: Journal contributions › Journal articles › Research › peer-review

Self-improvement for Computerized Adaptive Testing

Rudolph, Y., Neubauer, K. & Brefeld, U., 2026, Machine Learning and Knowledge Discovery in Databases - Research Track: European Conference, ECML PKDD 2025, Porto, Portugal, September 15–19, 2025, Proceedings. Ribeiro, R. P., Jorge, A. M., Soares, C., Gama, J., Pfahringer, B., Japkowicz, N., Larrañaga, P. & Abreu, P. H. (eds.). Cham: Springer International Publishing, Vol. 2. p. 70-86 17 p. (Lecture Notes in Computer Science; vol. 16014 LNCS).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

Documents

Links

Recently viewed

Activities

  1. Plenary lecture entitled: "Wavelet Packets for Applications in Signal Processing and Control Systems"
  2. Short course on numerical methods for stochastic processes
  3. I Am Behind the Screen: Understanding the Invisible Work of Content Moderators on Digital Platforms
  4. Nordic Seminar on Computational Mechanics - NSCM 2016
  5. Presentation of the paper entitled: "Classical PI Controllers with Anti-Windup Techniques Applied on Level Systems: An Interesting Case Study"
  6. 27st IEEE International Conference on Methods and Models in Automation an Robotics (MMAR)
  7. It's Time to Talk About Time Shaping Competence: A Framework for Addressing “Time” in ESE
  8. Towards a fully-automated adaptive e-learning environment: A predictive model for difficulty generating factors in gap-filling activities that target English tense-aspect-mood
  9. Fuzzy based control of a nonholonomic car-like robot for drive assistant systems
  10. SON 2020+2: International Workshop on Dynamics, Optimization, and Computation
  11. Unit Root & Cointegration Testing Conference 2005

Publications

  1. 'SPREAD THE APP, NOT THE VIRUS’ – AN EXTENSIVE SEM-APPROACH TO UNDERSTAND PANDEMIC TRACING APP USAGE IN GERMANY
  2. Simultaneous Constrained Adaptive Item Selection for Group-Based Testing
  3. Inversion of fuzzy neural networks for the reduction of noise in the control loop
  4. Age-related differences in processing visual device and task characteristics when using technical devices
  5. Enhancing Performance of Level System Modeling with Pseudo-Random Signals
  6. Neural Combinatorial Optimization on Heterogeneous Graphs
  7. Transformer with Tree-order Encoding for Neural Program Generation
  8. Lyapunov Convergence Analysis for Asymptotic Tracking Using Forward and Backward Euler Approximation of Discrete Differential Equations
  9. Mathematics in Robot Control for Theoretical and Applied Problems
  10. PI and Fuzzy Controllers for Non-Linear Systems
  11. Analysis And Comparison Of Dispatching RuleBased Scheduling In Dual-Resource Constrained Shop-Floor Scenarios
  12. Exploration strategies, performance, and error consequences when learning a complex computer task
  13. Lessons learned for spatial modelling of ecosystem services in support of ecosystem accounting
  14. How to support synchronous net-based learning discourses
  15. Construct Objectification and De-Objectification in Organization Theory
  16. Development and validation of a method for the determination of trace alkylphenols and phthalates in the atmosphere
  17. Recurrence quantificationanalysis as a general-purpose tool for bridging the gap between qualitative and quantitative analysis