Frederic Stahl
Frederic Stahl
Associate Professor, University of Reading, United Kingdom
Verified email at reading.ac.uk - Homepage
TitleCited byYear
A Survey of Data Mining Techniques for Social Media Analysis
M Adedoyin-Olowe, MM Gaber, F Stahl
arXiv preprint arXiv:1312.4617, 2013
962013
Data stream mining in ubiquitous environments: state‐of‐the‐art and current directions
MM Gaber, J Gama, S Krishnaswamy, JB Gomes, F Stahl
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 4 (2 …, 2014
412014
Pocket Data Mining: Big Data on Small Devices
MM Gaber, F Stahl, JB Gomes
Springer Publishing Company, Incorporated, 2014
39*2014
Pocket data mining: towards collaborative data mining in mobile computing environments
F Stahl, MM Gaber, M Bramer, PS Yu
Tools with Artificial Intelligence (ICTAI), 2010 22nd IEEE International …, 2010
362010
A rule dynamics approach to event detection in Twitter with its application to sports and politics
M Adedoyin-Olowe, MM Gaber, CM Dancausa, F Stahl, JB Gomes
Expert Systems with Applications 55, 351-360, 2016
342016
Computationally efficient induction of classification rules with the PMCRI and J-PMCRI frameworks
F Stahl, M Bramer
Knowledge-Based Systems 35, 49-63, 2012
322012
Scalable real-time classification of data streams with concept drift
M Tennant, F Stahl, O Rana, JB Gomes
Future Generation Computer Systems 75, 187-199, 2017
312017
Towards data warehousing and mining of protein unfolding simulation data
D Berrar, F Stahl, C Silva, JR Rodrigues, RMM Brito, W Dubitzky
Journal of clinical monitoring and computing 19 (4), 307-317, 2005
282005
An overview of the use of neural networks for data mining tasks
F Stahl, I Jordanov
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2 (3 …, 2012
262012
Towards cost-sensitive adaptation: When is it worth updating your predictive model?
I Žliobaitė, M Budka, F Stahl
Neurocomputing 150, 240-249, 2015
242015
TRCM: a methodology for temporal analysis of evolving concepts in Twitter
M Adedoyin-Olowe, MM Gaber, F Stahl
International Conference on Artificial Intelligence and Soft Computing, 135-145, 2013
242013
Jmax-pruning: A facility for the information theoretic pruning of modular classification rules
F Stahl, M Bramer
Knowledge-Based Systems 29, 12-19, 2012
222012
PMCRI: A parallel modular classification rule induction framework
F Stahl, M Bramer, M Adda
Machine Learning and Data Mining in Pattern Recognition, 148-162, 2009
222009
Computationally Efficient Rule-Based Classification for Continuous Streaming Data
T Le, F Stahl, JB Gomes, MM Gaber, G Di Fatta
Research and Development in Intelligent Systems XXXI, 21-34, 2014
212014
An overview of interactive visual data mining techniques for knowledge discovery
F Stahl, B Gabrys, MM Gaber, M Berendsen
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 3 (4 …, 2013
172013
Random prism: an alternative to random forests
F Stahl, M Bramer
Proceedings of Ai-2011: Research and Development in Intelligent Systems …, 2011
162011
Homogeneous and heterogeneous distributed classification for pocket data mining
F Stahl, M Gaber, P Aldridge, D May, H Liu, M Bramer, P Yu
Transactions on Large-Scale Data-and Knowledge-Centered Systems V, 183-205, 2012
132012
Scaling up data mining techniques to large datasets using parallel and distributed processing
F Stahl, MM Gaber, M Bramer
Business Intelligence and Performance Management, 243-259, 2013
122013
P-Prism: a computationally efficient approach to scaling up classification rule induction
F Stahl, M Bramer, M Adda
Artificial Intelligence in Theory and Practice II, 77-86, 2008
122008
Random Prism: a noise‐tolerant alternative to Random Forests
F Stahl, M Bramer
Expert Systems 31 (5), 411-420, 2014
112014
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