Georg Peters
| Job title | Honorary Professor |
|---|---|
| Research institute | School of Arts and Humanities |
| Faculty of Education and Arts |
Research outputs
Credit scoring using three-way decisions with probabilistic rough sets
Maldonado, Sebastian, Peters, Georg and Weber, Richard. (2020). Credit scoring using three-way decisions with probabilistic rough sets. Information Sciences. 507, pp. 700 - 714. https://doi.org/10.1016/j.ins.2018.08.001Journal article
A computer-based framework supporting education in STEM subjects
Peters, Georg, Rueckert, Tom and Seruga, Jan. (2019). A computer-based framework supporting education in STEM subjects. In In Hammoudi, Slimane, Smialek, Michal, Camp, Oliver and Filipe, Joaquim (Ed.). Enterprise information systems pp. 1-21 Springer Nature. https://doi.org/10.1007/978-3-030-26169-6_1Book chapter
dynXcube – categorizing dynamic data analysis
Peters, Georg and Weber, Richard. (2018). dynXcube – categorizing dynamic data analysis. Information Sciences. 463-464, pp. 21 - 32. https://doi.org/10.1016/j.ins.2018.06.026Journal article
A framework supporting literacy in mathematics and software programming
Peters, Georg, Rueckert, Tom and Seruga, Jan. (2018). A framework supporting literacy in mathematics and software programming. Portugal: Scitepress. pp. 497 - 506 https://doi.org/10.5220/0006629304970506Conference item
Some potentials of the R-Project Environment for teachers’ and students’ education in mathematics, algorithms’ programming and dynamic website development
Peters, Georg, Rueckert, Tom and Seruga, Jan. (2018). Some potentials of the R-Project Environment for teachers’ and students’ education in mathematics, algorithms’ programming and dynamic website development. United States of America: Association for he Advancement of Computing in Education (AACE). pp. 1816 - 1821Conference item
DCC : A framework for dynamic granular clustering
Peters, Georg and Weber, Richard. (2016). DCC : A framework for dynamic granular clustering. Granular Computing. 1, pp. 1-11. https://doi.org/10.1007/s41066-015-0012-zJournal article
A supply sided analysis of leading MooC platforms and universities
Peters, Georg and Seruga, Jan. (2016). A supply sided analysis of leading MooC platforms and universities. Knowledge Management and E-Learning. 8(1), pp. 158 - 181.Journal article
A comparative analysis of MOOC - Australia's position in the international education market
Peters, Georg, Sacker, Doreen and Seruga, Jan. (2015). A comparative analysis of MOOC - Australia's position in the international education market. Australasian Conference on Information Systems. Australia: University of South Australia. pp. 1 - 10Conference item
Is there any need for rough clustering?
Peters, Georg. (2015). Is there any need for rough clustering? Pattern Recognition Letters. 53, pp. 31 - 37. https://doi.org/10.1016/j.patrec.2014.11.003Journal article
Assessing rough classifiers
Peters, Georg. (2015). Assessing rough classifiers. Fundamenta Informaticae. 137, pp. 493 - 515. https://doi.org/10.3233/FI-2015-1191Journal article
Analysis of user-weighted pi rough k-means
Peters, Georg and Lingras, Pawan. (2014). Analysis of user-weighted pi rough k-means. In D Miao, W Pedrycz and D Slezak (Ed.). Rough Sets and Knowledge Technology. Switzerland: Springer. pp. 547 - 556 https://doi.org/10.1007/978-3-319-11740-9_50Conference item
Tweeting politicians: An analysis of the usage of a micro blogging system
Roth, Matthias, Peters, Georg and Seruga, Jan. (2014). Tweeting politicians: An analysis of the usage of a micro blogging system. In S. Hammoudi, J. Cordeiro and L. A. Maciaszek & J. Filipe (Ed.). Cham, Switzerland: Springer. pp. 351 - 364 https://doi.org/10.1007/978-3-319-09492-2_21Conference item
Rough clustering utilising the principle of indifference
Peters, Georg. (2014). Rough clustering utilising the principle of indifference. Information Sciences. 277, pp. 358 - 374. https://doi.org/10.1016/j.ins.2014.02.073Journal article
An illustrative comparison of rough k-Means to classical clustering approaches
Peters, Georg and Crespo, Fernando. (2013). An illustrative comparison of rough k-Means to classical clustering approaches. In D Ciucci, M Inuiguchi and Y Yao (Ed.). Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. Germany: Springer. pp. 337 - 344Conference item
Soft clustering: Fuzzy and rough approaches and their extensions and derivatives
Peters, Georg, Crespo, Fernando, Lingas, Pawan and Weber, Richard. (2013). Soft clustering: Fuzzy and rough approaches and their extensions and derivatives. International Journal of Approximate Reasoning. 54(2), pp. 307 - 322. https://doi.org/10.1016/j.ijar.2012.10.003Journal article
Some insights into the role of social media in political communication
Roth, Matthias, Peters, Georg and Seruga, Jan. (2013). Some insights into the role of social media in political communication. In S Hammoudi, L Maciaszek and J Cordeiro (Ed.). Proceedings of the 15th International Conference on Enterprise Information Systems. France: Institute for Systems and Technologies of Information, Control and Communication. pp. 353 - 362 https://doi.org/10.5220/0004418603510360Conference item
Dynamic clustering with soft computing
Peters, Georg and Weber, Richard. (2012). Dynamic clustering with soft computing. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 2(3), pp. 226 - 236. https://doi.org/10.1002/widm.1050Journal article
Tackling outliers in granular box regression
Peters, Georg and Lacic, Zdravko. (2012). Tackling outliers in granular box regression. Information Sciences. 212, pp. 44 - 56. https://doi.org/10.1016/j.ins.2012.05.006Journal article
Current trends in product lifecycle management
Staisch, Adam, Peters, Georg, Stueckl, Thomas and Seruga, Jan. (2012). Current trends in product lifecycle management. In J Lamp (Ed.). Proceedings of the 23rd Australasian Conference on Information Systems. Geelong, Victoria, Australia: Deakin University Press. pp. 1 - 10Conference item
Network Effects in the ERP Systems Market : An Analysis of the Implications of Business Intelligence and Cloud Computing
Peters, Georg and Seruga, Jan. (2012). Network Effects in the ERP Systems Market : An Analysis of the Implications of Business Intelligence and Cloud Computing. International Journal of Advanced Science and Technology. 43, pp. 105 - 114.Journal article
Network Effects in the ERP Systems Market: An Analysis of the Implications of Business Intelligence and Cloud Computing
Peters, Georg and Seruga, Jan. (2012). Network Effects in the ERP Systems Market: An Analysis of the Implications of Business Intelligence and Cloud Computing. International Journal of Advanced Science and Technology. 43, pp. 105 - 114.Journal article
Dynamic rough clustering and its applications
Peters, Georg, Weber, Richard and Nowatzke, René. (2012). Dynamic rough clustering and its applications. Applied Soft Computing Journal. 12(10), pp. 3193 - 3207. https://doi.org/10.1016/j.asoc.2012.05.015Journal article
Cross media and e-publishing
Rogobete, Carina, Peters, Georg and Seruga, Jan. (2012). Cross media and e-publishing. International Journal of u- and e- Service, Science and Technology. 5(2), pp. 17 - 29.Journal article
Rough clustering
Lingras, Pawan and Peters, Georg. (2011). Rough clustering. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. 1(1), pp. 64 - 72. https://doi.org/10.1002/widm.16Journal article
The effectiveness of electronic communication
Peters, Georg, Seruga, Jan and Zellmer, V.. (2011). The effectiveness of electronic communication. In B. White, P. Isaias and F. M. Santoro (Ed.). Proceedings of the IADIS International Conference WWW/Internet 2011. Brazil: IADIS Press. pp. 616 - 619Conference item
Analyzing IT business values – A Dominance based Rough Sets Approach perspective
Peters, Georg and Poon, Simon. (2011). Analyzing IT business values – A Dominance based Rough Sets Approach perspective. Expert Systems with Applications. 38(9), pp. 11120 - 11128. https://doi.org/10.1016/j.eswa.2011.02.157Journal article
Granular box regression
Peters, Georg. (2011). Granular box regression. IEEE Transactions on Fuzzy Systems. 19(6), pp. 1141 - 1152. https://doi.org/10.1109/TFUZZ.2011.2162416Journal article
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