Publications

Sort by: Date | Author | Title

Nissen, I. A., Walter, J. G., Charquero Ballester, M. & Bechmann, A. (2022). Digital Infrastructures of COVID-19 Misinformation: a new conceptual and analytical perspective on fact-checking. Digital Journalism, 10(5), 738-760. https://doi.org/10.1080/21670811.2022.2026795

Nissen, I. A., Mortensen, M. D., Sala, M., Walter, J. G., Charquero-Ballester, M., Sørensen, M. H., Nielbo, K. L. & Bechmann, A. (2021). Social media analysis with a focus on human rights on the internet. NGI FORWARD - H2020. https://doi.org/10.5281/zenodo.5795341

Nielsen, M. B., Kramp, G., Grønbæk, K., Bubak, M. (Ed.), van Albada, G. D. (Ed.), Sloot, P. M. A. (Ed.) & Dongarra, J. (Ed.) (2004). Mobile Augmented Reality Support for Architects Based on Feature Tracking Techniques. In Computational Science - ICCS 2004, 4th International Conference, Kraków, Poland, June 6-9, 2004, Part III (3038 i Lecture Notes in Computer Science ed., pp. 921-928)

Nielsen, J., Grønbæk, K. & Lykke-Olesen, A. (2005). Vision Based Simultaneous Multi Object Tracking on Semi-Transparent Surfaces. (Patent No. PA 2005 00795).

Nielsen, J. & Grønbæk, K. (2006). MultiLightTracker: Vision based simultaneous multi object tracking on semi-transparent surfaces. In Proceedings of the Conference on Computer Vision Theory and Applications Institute for Systems and Technologies of Information, Control and Communication.

Nielsen, S. D. I., Christensen, M. S., Roepstorff, A., Sinkjær, T., Vingborg, R. J. & Grey, M. J. (2012). Interaction of electrical stimulation and voluntary hand movement in SII and the cerebellum during simulated therapeutic Functional Electrical Stimulation in Healthy Adults. Human Brain Mapping, 33(1), 40-49. https://doi.org/10.1002/hbm.21191

Nielsen, J., Grønbæk, K. & Lykke-Olesen, A. (2005). MultiLightTracker: Vision Based Simultaneous Multi Object Tracking on Semi-Transparent Surfaces. Computer programme

Nielsen, M. & Grønbæk, K. (2015). PivotViz: Interactive Visual Analysis of Multidimensional Library Transaction Data. In Proceedings of the 15th ACM/IEEE-CS Joint Conference on Digital Libraries, JCDL '15 : Large, Dynamic and Ubiquitous –The Era of the Digital Library (pp. 139-142). Association for Computing Machinery. https://doi.org/10.1145/2756406.2756937

Nielsen, M. & Grønbæk, K. (2015). Towards highly affine visualizations of consumption data from buildings. In IVAPP 2015 - 6th International Conference on Information Visualization Theory and Applications; VISIGRAPP, Proceedings (pp. 247-255). SCITEPRESS Digital Library.

Nielsen, M., Kjærgaard, M. B. & Grønbæk, K. (2013). Exploring Interaction Techniques and Task Types for Direct-Touch as Input Modality. Poster session presented at VAST Infovis Scivis, Atlanta, Georgia, United States.

Nielsen, M., Brewer, R. S. & Grønbæk, K. (2016). Supporting interactive visual analytics of energy behavior in buildings through affine visualizations. In Proceedings of the 28th Australian Computer-Human Interaction Conference, OzCHI 2016 (pp. 238-247). Association for Computing Machinery. https://doi.org/10.1145/3010915.3010950

Nielsen, M., Elmqvist, N. & Grønbæk, K. (2016). Scribble query: fluid touch brushing for multivariate data visualization. In Proceedings of the 28th Australian Computer-Human Interaction Conference, OzCHI 2016 (pp. 381-390). Association for Computing Machinery. https://doi.org/10.1145/3010915.3010951

Nielsen, J. & Grønbæk, K. (2006). Multilighttracker: Vision based multi object tracking on semi-transparent surfaces. In VISAPP 2006 - Proceedings of the 1st International Conference on Computer Vision Theory and Applications (pp. 245-252)

Nielsen, J. H. & Mønster, D. (2021). In the Eye of the Beholder: Using Eye Tracking to Understand the Causal Influence of Governance Institutions on Attention. https://doi.org/10.31235/osf.io/9v6n7

Nielsen, J. H. & Mønster, D. (2021). The Affective Style of Politics: Evidence from Surveys and Laboratory Experiments. SocArXiv. https://doi.org/10.17605/OSF.IO/FJ6DZ

Nielsen, L. H., Roepstorff, A. & Petersen, M. B. (2022). Danskernes Adfærd og Holdninger Under Corona-Pandemien. Århus Universitet. https://hope-project.dk/#/reports/danskernes_adfaerd_og_holdninger/versions/10-03-2022

Nielsen, L. H., Roepstorff, A. & Petersen, M. B. (2022). Hvad kan vi lære om kriseadfærd fra corona-pandemien? Århus Universitet. https://hope-project.dk/#/reports/danskernes_adfaerd_og_holdninger

Nielbo, K. L., Vahlstrup, P. B. & Bechmann, A. (2020). Sociocultural trend signatures in minimal persistence and past novelty. Abstract from DH2020, Ottawa, Ontario, Canada.

Nielbo, K. L., Baglini, R. B., Vahlstrup, P. B., Enevoldsen, K. C., Bechmann, A. & Roepstorff, A. (2021). News Information Decoupling: An Information Signature of Catastrophes in Legacy News Media. Paper presented at EADH2021 "Interdisciplinary Perspectives on Data", Krasnoyarsk, Russian Federation. http://adsabs.harvard.edu/abs/2021arXiv210102956N

Nielbo, K. L., Vahlstrup, P. B., Bechmann, A. & Gao, J. (2020). Trend reservoir detection: Minimal persistence and resonant behavior of trends in social media. CEUR Workshop Proceedings, 2723, 290-297.

Nielbo, K. L., Hæstrup, F., Enevoldsen, K., Vahlstrup, P. B., Baglini, R. B. & Roepstorff, A. (2021). When no news is bad news--Detection of negative events from news media content. ArXiv. https://arxiv.org/pdf/2102.06505.pdf

Nielbo, K. L., Baglini, R. B. & Roepstorff, A. (2022). Information Decoupling as a Pandemic Signature in News Media. Abstract from Digital Humanities in the Nordic and Baltic Countries Conference (DHNB 2022), Uppsala, Sweden. https://dhnb.eu/wp-content/uploads/2022/03/DHNB2022_book_of_abstracts.pdf

Nielbo, K. L., Baglini, R. B., Vahlstrup, P. B., Enevoldsen, K. C., Bechmann, A. & Roepstorff, A. (2021). News Information Decoupling: An Information Signature of Catastrophes in Legacy News Media.

Nielbo, K. L., Enevoldsen, K., Baglini, R. B., Fano, E., Roepstorff, A. & Gao, J. (2023). Pandemic news information uncertainty: News dynamics mirror differential response strategies to COVID-19. P L o S One, 18(1 ), Article e0278098. https://doi.org/10.1371/journal.pone.0278098

Nielbo, K. L., Hæstrup, F., Enevoldsen, K., Vahlstrup, P. B., Baglini, R. B. & Roepstorff, A. (2022). When No News is Bad News. News-based Change Detection During COVID-19. DH Benelux Journal, 4, 107-120. https://doi.org/10.17613/03ds-9973

Nguyen, H. V., Gopalkrishnan, V. & Assent, I. (2011). An Unbiased Distance-based Outlier Detection Approach for High-dimensional Data. Lecture Notes in Computer Science, 6587, 138-152. https://doi.org/10.1007/978-3-642-20149-3_12

Nguyen, V., Versyp, O., Cox, C. & Fusaroli, R. (2022). A systematic review and Bayesian meta-analysis of the development of turn taking in adult-child vocal interactions. Child Development, 93(4), 1181-1200. https://doi.org/10.1111/cdev.13754

Neerbek, J., Assent, I. & Dolog, P. (2017). TABOO: Detecting unstructured sensitive information using recursive neural networks. In Proceedings - 2017 IEEE 33rd International Conference on Data Engineering, ICDE 2017 (pp. 1399-1400). Article 7930091 IEEE Computer Society Press. https://doi.org/10.1109/ICDE.2017.195

Neerbek, J., Dolog, P. & Assent, I. (2019). Selective Training: A Strategy for Fast Backpropagation on Sentence Embeddings. In Q. Yang, M.-L. Zhang, Z. Gong, S.-J. Huang & Z.-H. Zhou (Eds.), Advances in Knowledge Discovery and Data Mining - 23rd Pacific-Asia Conference, PAKDD 2019, Proceedings: PAKDD '19 (pp. 40-53). Springer. https://doi.org/10.1007/978-3-030-16142-2_4

Neerbek, J., Assent, I. & Dolog, P. (2018). Detecting Complex Sensitive Information via Phrase Structure in Recursive Neural Networks. In D. Phung, V. S. Tseng, G. I. Webb, B. Ho, M. Ganji & L. Rashidi (Eds.), Advances in Knowledge Discovery and Data Mining - 22nd Pacific-Asia Conference, PAKDD 2018, Proceedings: PAKDD '18 (Vol. 10939, pp. 373-385). Springer VS. https://doi.org/10.1007/978-3-319-93040-4_30

Neerbek, J., Eskildsen, M., Dolog, P. & Assent, I. (2020). A real-world data resource of complex sensitive sentences based on documents from the Monsanto trial. In N. Calzolari, F. Bechet, P. Blache, K. Choukri, C. Cieri, T. Declerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk & S. Piperidis (Eds.), LREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings (pp. 1258-1267). European Language Resources Association.

Nagy, S., Mansour, H. & Presser, M. (2018). Case Study of IoT as a Driver for Business Model Innovation in the Wind Industry. 74-79. Paper presented at IEEE Internet of Things: 2018 IEEE 4th World Forum on Internet of Things, Singapore.

Nagenborg, M., Albrechtslund, A., Klamt, M. & Murakami Wood, D. (2010). On "ICT and the City". International Review of Information Ethics, 12(3), 2-6.

Nagenborg, M., Albrechtslund, A., Klamt, M. & Murakami Wood, D. (2010). Editorial: On IRIE vol. 12. International Review of Information Ethics, 12(3), 1.

Nagenborg, M., Albrechtslund, A., Klamt, M. & Murakami Wood, D. (Eds.) (2010). ICT and the City. International Review of Information Ethics, 12(3).

Nagatsu, M., Larsen, K., Karabegovic, M., Székely, M., Mønster, D. & Michael, J. (2018). Making good cider out of bad apples – Signaling expectations boosts cooperation among would-be free riders. Judgment and Decision Making, 13(1), 137-149. http://journal.sjdm.org/16/161219/jdm161219.pdf

Müller, E., Assent, I., Günnemann, S., Gerwert, P., Hannen, M., Jansen, T. & Seidl, T. (2011). A Framework for Evaluation and Exploration of Clustering Algorithms in Subspaces of High Dimensional Databases. In T. Härder, W. Lehner, B. Mitschang, H. Schöning & H. Schwarz (Eds.), Proceedings of the 14th GI Conference on Database Systems for Business, Technology, and the Web (BTW 2011) (pp. 347-366). Gesellschaft für Informatik e.V..

Müller, E., Assent, I., Günnemann, S. & Seidl, T. (2011). Scalable Density-Based Subspace Clustering. In Proceedings of the 20th ACM international conference on Information and knowledge management (pp. 1077-1086). Association for Computing Machinery. https://doi.org/10.1145/2063576.2063733

Müller, E., Assent, I., Krieger, R., Günnemann, S. & Seidl, T. (2009). DensEst: Density Estimation for Data Mining in High Dimensional Spaces. In Proceedings of the Ninth SIAM International Conference on Data Mining (pp. 175-186) http://www.siam.org/proceedings/datamining/2009/dm09.php

Müller, E., Günnemann, S., Assent, I. & Seidl, T. (2009). Evaluating Clustering in Subspace Projections of High Dimensional Data. V L D B Journal, (1), 1270-1281. http://www.informatik.uni-trier.de/~ley/db/journals/pvldb/pvldb2.html

Müller, E., Assent, I., Günnemann, S., Krieger, R. & Seidl, T. (2009). Relevant Subspace Clustering: Mining the Most Interesting Non-Redundant Concepts in High-Dimensional Data. In Proc. IEEE International Conference on Data Mining (ICDM 2009) (pp. 377-386) https://doi.org/10.1109/ICDM.2009.10

Müller, E., Assent, I., Günnemann, S. & Seidl, T. (2009). OpenSubspace: An Open Source Framework for Evaluation and Exploration of Subspace Clustering Algorithms in WEKA. In Proceedings of OSDM 2009 (pp. 1-12) http://osdm09.togaware.com/

Müller, E., Assent, I., Steinhausen, U. & Seidl, T. (2008). OutRank: ranking outliers in high dimensional data. In IEEE 24th International Conference on Data Engineering Workshop, 2008. ICDEW 2008 (pp. 600-603) https://doi.org/10.1109/ICDEW.2008.4498387

Müller, E., Assent, I., Günnemann, S., Seidl, T. & Dy, J. (2015). MultiClust special issue on discovering, summarizing and using multiple clusterings. Machine Learning, 98(1-2), 1-5. https://doi.org/10.1007/s10994-014-5445-0

Muller, E., Assent, I., Iglesias, P., Mülle, Y. & Böhm, K. B. (2012). Outlier Ranking via Subspace Analysis in Multiple Views of the Data. In Proceedings of the 12th IEEE International Conference on Data Mining, ICDM (pp. 529 - 538 ). IEEE Communications Society. https://doi.org/10.1109/ICDM.2012.112

Mortensen, M. L., Chester, S., Assent, I. & Magnani, M. (2015). Efficient caching for constrained skyline queries. In International Conference on Extending Database Technology (EDBT 2015) (pp. 337-348). openproceedings.org. https://doi.org/10.5441/002/edbt.2015.30

Mortensen, J., Siegfredsen, N. & Bechmann, A. (2023). Datafication in Human-Machine Communication between representation and preferences: an experiment of non-binary gender representation in voice-controlled assistants. In Handbook of Human-Machine Communication (pp. 327-334). SAGE Publications.

Moradan, A., Draganov, A., Mottin, D. & Assent, I. (2021). UCoDe: Unified Community Detection with Graph Convolutional Networks.

Moradan, A., Draganov, A., Mottin, D. & Assent, I. (2023). UCoDe: unified community detection with graph convolutional networks. Machine Learning, 112(12), 5057-5080. https://doi.org/10.1007/s10994-023-06402-0

Mønster, D. & Madsen, J. (1996). Strangelets with finite entropy. Physical Review D, 53(9), R4719-R4722. https://doi.org/10.1103/PhysRevD.53.R4719

Displaying results 401 to 450 out of 1560

Revised 24.04.2023