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Mining positional data streams

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

Standard

Mining positional data streams. / Haase, Jens; Brefeld, Ulf.

New Frontiers in Mining Complex Patterns. Springer, 2015. p. 102-116.

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

Harvard

Haase, J & Brefeld, U 2015, Mining positional data streams. in New Frontiers in Mining Complex Patterns. Springer, pp. 102-116, 3rd International Workshop on New Frontiers in Mining Complex Patterns - NFMCP 2014, Nancy, France, 19.09.14. https://doi.org/10.1007/978-3-319-17876-9_7

APA

Haase, J., & Brefeld, U. (2015). Mining positional data streams. In New Frontiers in Mining Complex Patterns (pp. 102-116). Springer. https://doi.org/10.1007/978-3-319-17876-9_7

Vancouver

Haase J, Brefeld U. Mining positional data streams. In New Frontiers in Mining Complex Patterns. Springer. 2015. p. 102-116 doi: 10.1007/978-3-319-17876-9_7

Bibtex

@inbook{a4f6db1289c04684bd8c28473bb637bf,
title = "Mining positional data streams",
abstract = "We study frequent pattern mining from positional data streams. Existing approaches require discretised data to identify atomic events and are not applicable in our continuous setting. We propose an efficient trajectory-based preprocessing to identify similar movements and a distributed pattern mining algorithm to identify frequent trajectories. We empirically evaluate all parts of the processing pipeline.",
keywords = "Informatics, Pattern Mining, Dynamic Time Warping, Positional Data, Frequent Episode, Event Stream, Business informatics",
author = "Jens Haase and Ulf Brefeld",
year = "2015",
doi = "10.1007/978-3-319-17876-9_7",
language = "English",
isbn = "978-3-319-17875-2",
pages = "102--116",
booktitle = "New Frontiers in Mining Complex Patterns",
publisher = "Springer",
address = "Germany",
note = "3rd International Workshop on New Frontiers in Mining Complex Patterns - NFMCP 2014, NFMCP 2014 ; Conference date: 19-09-2014 Through 19-09-2014",

}

RIS

TY - CHAP

T1 - Mining positional data streams

AU - Haase, Jens

AU - Brefeld, Ulf

N1 - Conference code: 3

PY - 2015

Y1 - 2015

N2 - We study frequent pattern mining from positional data streams. Existing approaches require discretised data to identify atomic events and are not applicable in our continuous setting. We propose an efficient trajectory-based preprocessing to identify similar movements and a distributed pattern mining algorithm to identify frequent trajectories. We empirically evaluate all parts of the processing pipeline.

AB - We study frequent pattern mining from positional data streams. Existing approaches require discretised data to identify atomic events and are not applicable in our continuous setting. We propose an efficient trajectory-based preprocessing to identify similar movements and a distributed pattern mining algorithm to identify frequent trajectories. We empirically evaluate all parts of the processing pipeline.

KW - Informatics

KW - Pattern Mining

KW - Dynamic Time Warping

KW - Positional Data

KW - Frequent Episode

KW - Event Stream

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=84931056379&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-17876-9_7

DO - 10.1007/978-3-319-17876-9_7

M3 - Article in conference proceedings

AN - SCOPUS:84931056379

SN - 978-3-319-17875-2

SP - 102

EP - 116

BT - New Frontiers in Mining Complex Patterns

PB - Springer

T2 - 3rd International Workshop on New Frontiers in Mining Complex Patterns - NFMCP 2014

Y2 - 19 September 2014 through 19 September 2014

ER -

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Research output: Contributions to collected editions/works › Chapter

Data practices in apps from Brazil: What do privacy policies inform us about?

Quadros dos Reis, V., Rabello, M. E. R., Lima, A. C., Jardim, G. P. S., Fernandes, E. R. & Brefeld, U., 10.02.2023, In: Journal on Interactive Systems. 14, 1, p. 1-8 8 p.

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

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Fadel, S., Paulsen, T. & Brefeld, U., 09.2023, 20th Machine Learning on Graphs workshop.

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

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Sarhan, N., Wilms, C., Closius, V., Brefeld, U. & Frintrop, S., 08.10.2023, 2023 IEEE International Conference on Image Processing, ICIP 2023 - Proceedings: Proceedings. Piscataway: IEEE Electromagnetic Compatibility Society, p. 2555-2559 5 p. (Proceedings - International Conference on Image Processing, ICIP).

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

Masked Autoencoder Pretraining for Event Classification in Elite Soccer

Rudolph, Y. & Brefeld, U., 26.02.2024, Machine Learning and Data Mining for Sports Analytics: 10th International Workshop, MLSA 2023, Revised Selected Papers. Brefeld, U., Davis, J., Van Haaren, J. & Zimmermann, A. (eds.). Cham: Springer Nature Switzerland AG, p. 24-35 12 p. (Communications in Computer and Information Science; vol. 2035).

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

DOI