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Assessing User Behavior by Mouse Movements

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

Standard

Assessing User Behavior by Mouse Movements. / Matthiesen, Jennifer Jorina; Brefeld, Ulf.
HCI International 2020 - Posters - : 22nd International Conference, HCII 2020, Proceedings. ed. / Constantine Stephanidis; Margherita Antona. Cham: Springer Verlag, 2020. p. 68-75 (Communications in Computer and Information Science; Vol. 1224 CCIS).

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

Harvard

Matthiesen, JJ & Brefeld, U 2020, Assessing User Behavior by Mouse Movements. in C Stephanidis & M Antona (eds), HCI International 2020 - Posters - : 22nd International Conference, HCII 2020, Proceedings. Communications in Computer and Information Science, vol. 1224 CCIS, Springer Verlag, Cham, pp. 68-75, 22nd International Conference on Human-Computer Interaction - HCII 2020, Copenhagen, Denmark, 19.07.20. https://doi.org/10.1007/978-3-030-50726-8_9

APA

Matthiesen, J. J., & Brefeld, U. (2020). Assessing User Behavior by Mouse Movements. In C. Stephanidis, & M. Antona (Eds.), HCI International 2020 - Posters - : 22nd International Conference, HCII 2020, Proceedings (pp. 68-75). (Communications in Computer and Information Science; Vol. 1224 CCIS). Springer Verlag. https://doi.org/10.1007/978-3-030-50726-8_9

Vancouver

Matthiesen JJ, Brefeld U. Assessing User Behavior by Mouse Movements. In Stephanidis C, Antona M, editors, HCI International 2020 - Posters - : 22nd International Conference, HCII 2020, Proceedings. Cham: Springer Verlag. 2020. p. 68-75. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-50726-8_9

Bibtex

@inbook{efd68aa5f682420ba7ff2367101771ce,
title = "Assessing User Behavior by Mouse Movements",
abstract = "In this working paper, we study user identification via mouse movement. Instead of treating the problem as a multi-class classification task, we cast user identification as a one-class problem and propose to learn an individual model for every user. Preliminary empirical results show that our approach works for some but not all users. We report on lessons learned.",
keywords = "Mouse movement, User behavior, User identification, Informatics",
author = "Matthiesen, {Jennifer Jorina} and Ulf Brefeld",
year = "2020",
doi = "10.1007/978-3-030-50726-8_9",
language = "English",
isbn = "9783030507251",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "68--75",
editor = "Constantine Stephanidis and Margherita Antona",
booktitle = "HCI International 2020 - Posters -",
address = "Germany",
note = "22nd International Conference on Human-Computer Interaction - HCII 2020, HCII2020 ; Conference date: 19-07-2020 Through 24-07-2020",
url = "http://2020.hci.international/",

}

RIS

TY - CHAP

T1 - Assessing User Behavior by Mouse Movements

AU - Matthiesen, Jennifer Jorina

AU - Brefeld, Ulf

N1 - Conference code: 22

PY - 2020

Y1 - 2020

N2 - In this working paper, we study user identification via mouse movement. Instead of treating the problem as a multi-class classification task, we cast user identification as a one-class problem and propose to learn an individual model for every user. Preliminary empirical results show that our approach works for some but not all users. We report on lessons learned.

AB - In this working paper, we study user identification via mouse movement. Instead of treating the problem as a multi-class classification task, we cast user identification as a one-class problem and propose to learn an individual model for every user. Preliminary empirical results show that our approach works for some but not all users. We report on lessons learned.

KW - Mouse movement

KW - User behavior

KW - User identification

KW - Informatics

UR - http://www.scopus.com/inward/record.url?scp=85088752669&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-50726-8_9

DO - 10.1007/978-3-030-50726-8_9

M3 - Article in conference proceedings

AN - SCOPUS:85088752669

SN - 9783030507251

T3 - Communications in Computer and Information Science

SP - 68

EP - 75

BT - HCI International 2020 - Posters -

A2 - Stephanidis, Constantine

A2 - Antona, Margherita

PB - Springer Verlag

CY - Cham

T2 - 22nd International Conference on Human-Computer Interaction - HCII 2020

Y2 - 19 July 2020 through 24 July 2020

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

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