Java Sorting Programs

Paaßen B (2016) : Bielefeld University. doi:10.4119/unibi/2900684.

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Abstract / Bemerkung
This is a dataset of 126 Java computer programs, all sorting an array of integers in ascending order. The programs have been gathered from the web in 2015 as part of the DFG funded project _Learning Feedback for Dynamic Tutoring Systems_ (FIT) with grant number HA 2719/6-1. It is meant as a benchmark dataset for methods working on clustering and/or classification of structured data (sequences, trees or graphs). For copyright reasons, we can not provide the source code directly. Instead, this dataset contains meta data about the data points as well as pre-calculated distance matrices.
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This Java Sorting Programs is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0. Any rights in individual contents of the database are licensed under the Database Contents License: http://opendatacommons.org/licenses/dbcl/1.0/
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Paaßen B. (2016): Java Sorting Programs. Bielefeld University. doi:10.4119/unibi/2900684.
Paaßen, B. (2016). Java Sorting Programs. Bielefeld University. doi:10.4119/unibi/2900684
Paaßen, B. (2016). Java Sorting Programs. Bielefeld University. doi:10.4119/unibi/2900684.
Paaßen, B., 2016. Java Sorting Programs. Bielefeld University. doi:10.4119/unibi/2900684
B. Paaßen, Java Sorting Programs. Bielefeld University, 2016. doi:10.4119/unibi/2900684.
Paaßen, B.: Java Sorting Programs. Bielefeld University (2016). doi:10.4119/unibi/2900684.
Paaßen, Benjamin. Java Sorting Programs. Bielefeld University, 2016. doi:10.4119/unibi/2900684
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2017-10-05T08:29:24Z
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229.07 KB
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OA Open Access
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Material in PUB:
forms.relation..display
Adaptive structure metrics for automated feedback provision in intelligent tutoring systems
Paaßen B, Mokbel B, Hammer B (2016)
Neurocomputing 192(SI): 3-13.
forms.relation..display
Metric learning for sequences in relational LVQ
Mokbel B, Paaßen B, Schleif F-M, Hammer B (2015)
Neurocomputing 169(SI): 306-322.
forms.relation..display
Execution Traces as a Powerful Data Representation for Intelligent Tutoring Systems for Programming
Paaßen B, Jensen J, Hammer B (2016)
In: Proceedings of the 9th International Conference on Educational Data Mining. Barnes T, Chi M, Feng M (Eds); Raleigh, North Carolina, USA: International Educational Datamining Society: 183-190.
forms.relation..display
Gaussian process prediction for time series of structured data
Paaßen B, Göpfert C, Hammer B (2016)
In: Proceedings of the ESANN, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Verleysen M (Ed); Louvain-la-Neuve: Ciaco - i6doc.com: 41--46.

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