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ORCIDMohamed Medhat Gaber
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- affiliation: Birmingham City University, UK
- affiliation: Galala University, Egypt
- affiliation (former): Robert Gordon University
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2020 – today
- 2021
[j62]Asmaa Abbas, Mohammed M. Abdelsamea
, Mohamed Medhat Gaber:
Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network. Appl. Intell. 51(2): 854-864 (2021)- [j61]Zakaria Senousy, Mohammed M. Abdelsamea, Mona Mostafa Mohamed, Mohamed Medhat Gaber:
3E-Net: Entropy-Based Elastic Ensemble of Deep Convolutional Neural Networks for Grading of Invasive Breast Carcinoma Histopathological Microscopic Images. Entropy 23(5): 620 (2021) - [j60]Frederic T. Stahl, Thien Le, Atta Badii, Mohamed Medhat Gaber:
A Frequent Pattern Conjunction Heuristic for Rule Generation in Data Streams. Inf. 12(1): 24 (2021) - [j59]Asmaa Abbas, Mohammed M. Abdelsamea, Mohamed Medhat Gaber:
4S-DT: Self-Supervised Super Sample Decomposition for Transfer Learning With Application to COVID-19 Detection. IEEE Trans. Neural Networks Learn. Syst. 32(7): 2798-2808 (2021) - [j58]Amna Dridi, Mohamed Medhat Gaber, R. Muhammad Atif Azad, Jagdev Bhogal:
Scholarly data mining: A systematic review of its applications. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 11(2) (2021) - [c75]Nicole P. Mugova, Mohammed M. Abdelsamea, Mohamed Medhat Gaber:
On The Effect Of Decomposition Granularity On DeTraC For COVID-19 Detection Using Chest X-Ray Images. ECMS 2021: 29-34 - [c74]Saif Alzubi, Frederic T. Stahl, Mohamed Medhat Gaber:
Towards Intrusion Detection Of Previously Unknown Network Attacks. ECMS 2021: 35-41 - 2020
- [j57]Asmaa Abbas, Mohammed M. Abdelsamea, Mohamed Medhat Gaber:
DeTrac: Transfer Learning of Class Decomposed Medical Images in Convolutional Neural Networks. IEEE Access 8: 74901-74913 (2020) - [j56]Khadijah M. Hanga, Yevgeniya Kovalchuk, Mohamed Medhat Gaber:
A Graph-Based Approach to Interpreting Recurrent Neural Networks in Process Mining. IEEE Access 8: 172923-172938 (2020) - [j55]Julian Hatwell, Mohamed Medhat Gaber, R. Muhammad Atif Azad:
CHIRPS: Explaining random forest classification. Artif. Intell. Rev. 53(8): 5747-5788 (2020) - [j54]Khaled Fawagreh, Mohamed Medhat Gaber:
eGAP: An Evolutionary Game Theoretic Approach to Random Forest Pruning. Big Data Cogn. Comput. 4(4): 37 (2020) - [j53]Khaled Fawagreh, Mohamed Medhat Gaber:
Resource-efficient fast prediction in healthcare data analytics: A pruned Random Forest regression approach. Computing 102(5): 1187-1198 (2020) - [j52]Hossein Ghomeshi, Mohamed Medhat Gaber, Yevgeniya Kovalchuk:
A non-canonical hybrid metaheuristic approach to adaptive data stream classification. Future Gener. Comput. Syst. 102: 127-139 (2020) - [j51]Julian Hatwell, Mohamed Medhat Gaber, R. Muhammad Atif Azad:
Ada-WHIPS: explaining AdaBoost classification with applications in the health sciences. BMC Medical Informatics Decis. Mak. 20(1): 250 (2020) - [j50]Zahraa S. Abdallah, Mohamed Medhat Gaber:
Co-eye: a multi-resolution ensemble classifier for symbolically approximated time series. Mach. Learn. 109(11): 2029-2061 (2020) - [i12]Asmaa Abbas, Mohammed M. Abdelsamea, Mohamed Medhat Gaber:
Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network. CoRR abs/2003.13815 (2020) - [i11]Lorraine Chambers, Mohamed Medhat Gaber, Zahraa S. Abdallah:
DeepStreamCE: A Streaming Approach to Concept Evolution Detection in Deep Neural Networks. CoRR abs/2004.04116 (2020) - [i10]Besher Alhalabi, Mohamed Medhat Gaber, Shadi Basurra:
Prune2Edge: A Multi-Phase Pruning Pipelines to Deep Ensemble Learning in IIoT. CoRR abs/2004.04710 (2020) - [i9]Zahraa S. Abdallah, Mohamed Medhat Gaber:
Co-eye: A Multi-resolution Symbolic Representation to TimeSeries Diversified Ensemble Classification. CoRR abs/2004.06668 (2020) - [i8]Hansi Hettiarachchi, Mariam Adedoyin-Olowe, Jagdev Bhogal, Mohamed Medhat Gaber:
Embed2Detect: Temporally Clustered Embedded Words for Event Detection in Social Media. CoRR abs/2006.05908 (2020) - [i7]Asmaa Abbas, Mohammed M. Abdelsamea, Mohamed Medhat Gaber:
4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection. CoRR abs/2007.11450 (2020)
2010 – 2019
- 2019
- [j49]Fatima Abdallah, Shadi Basurra, Mohamed Medhat Gaber:
A Non-Intrusive Heuristic for Energy Messaging Intervention Modeled Using a Novel Agent-Based Approach. IEEE Access 7: 1627-1646 (2019) - [j48]Hossein Ghomeshi, Mohamed Medhat Gaber, Yevgeniya Kovalchuk:
RED-GENE: An Evolutionary Game Theoretic Approach to Adaptive Data Stream Classification. IEEE Access 7: 173944-173954 (2019) - [j47]Amna Dridi, Mohamed Medhat Gaber, R. Muhammad Atif Azad, Jagdev Bhogal:
Leap2Trend: A Temporal Word Embedding Approach for Instant Detection of Emerging Scientific Trends. IEEE Access 7: 176414-176428 (2019) - [j46]Hossein Ghomeshi, Mohamed Medhat Gaber, Yevgeniya Kovalchuk:
EACD: evolutionary adaptation to concept drifts in data streams. Data Min. Knowl. Discov. 33(3): 663-694 (2019) - [j45]Alfredo Cuzzocrea, Mohamed Medhat Gaber, Edoardo Fadda, Giorgio Mario Grasso:
An innovative framework for supporting big atmospheric data analytics via clustering-based spatio-temporal analysis. J. Ambient Intell. Humaniz. Comput. 10(9): 3383-3398 (2019) - [j44]Mohamed Medhat Gaber, Adel Aneiba, Shadi Basurra, Oliver Batty, Ahmed M. Elmisery, Yevgeniya Kovalchuk, Muhammad Habib Ur Rehman:
Internet of Things and data mining: From applications to techniques and systems. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 9(3) (2019) - [c73]Mona Nabil Demaidi, Mohamed Medhat Gaber:
TONE: A Method for Terminological Ontology Evaluation. ArabWIC 2019: 14:1-14:10 - [c72]Amna Dridi, Mohamed Medhat Gaber, R. Muhammad Atif Azad, Jagdev Bhogal:
DeepHist: Towards a Deep Learning-based Computational History of Trends in the NIPS. IJCNN 2019: 1-8 - [c71]Besher Alhalabi, Mohamed Medhat Gaber, Shadi Basurra:
EnSyth: A Pruning Approach to Synthesis of Deep Learning Ensembles. SMC 2019: 3466-3473 - [i6]Besher Alhalabi, Mohamed Medhat Gaber, Shadi Basurra:
EnSyth: A Pruning Approach to Synthesis of Deep Learning Ensembles. CoRR abs/1907.09286 (2019) - [i5]Safwan Shatnawi, Mohamed Medhat Gaber, Mihaela Cocea:
A Heuristically Modified FP-Tree for Ontology Learning with Applications in Education. CoRR abs/1910.13561 (2019) - 2018
- [j43]Mona Nabil Demaidi, Mohamed Medhat Gaber, Nick Filer:
OntoPeFeGe: Ontology-Based Personalized Feedback Generator. IEEE Access 6: 31644-31664 (2018) - [j42]Mahmut Yazici, Shadi Basurra, Mohamed Medhat Gaber:
Edge Machine Learning: Enabling Smart Internet of Things Applications. Big Data Cogn. Comput. 2(3): 26 (2018) - [j41]Zahraa Said Abdallah, Mohamed Medhat Gaber, Bala Srinivasan, Shonali Krishnaswamy:
Activity Recognition with Evolving Data Streams: A Review. ACM Comput. Surv. 51(4): 71:1-71:36 (2018) - [j40]Ahmed Hussein, Eyad Elyan, Mohamed Medhat Gaber, Chrisina Jayne:
Deep imitation learning for 3D navigation tasks. Neural Comput. Appl. 29(7): 389-404 (2018) - [c70]Amna Dridi, Mohamed Medhat Gaber, R. Muhammad Atif Azad, Jagdev Bhogal:
k-NN Embedding Stability for word2vec Hyper-Parametrisation in Scientific Text. DS 2018: 328-343 - [c69]Fatima Abdallah, Shadi Basurra, Mohamed Medhat Gaber:
Cascading Probability Distributions in Agent-Based Models: An Application to Behavioural Energy Wastage. ICAISC (2) 2018: 489-503 - [c68]Fatima Abdallah, Shadi Basurra, Mohamed Medhat Gaber:
An Agent-Based Collective Model to Simulate Peer Pressure Effect on Energy Consumption. ICCCI (1) 2018: 283-296 - [c67]Diana Haidar, Mohamed Medhat Gaber:
Adaptive One-Class Ensemble-based Anomaly Detection: An Application to Insider Threats. IJCNN 2018: 1-9 - [i4]Diana Haidar, Mohamed Medhat Gaber, Yevgeniya Kovalchuk:
AnyThreat: An Opportunistic Knowledge Discovery Approach to Insider Threat Detection. CoRR abs/1812.00257 (2018) - 2017
- [j39]Ahmed Hussein, Mohamed Medhat Gaber, Eyad Elyan, Chrisina Jayne:
Imitation Learning: A Survey of Learning Methods. ACM Comput. Surv. 50(2): 21:1-21:35 (2017) - [j38]Thien Le, Frederic T. Stahl, Mohamed Medhat Gaber, João Bártolo Gomes, Giuseppe Di Fatta:
On expressiveness and uncertainty awareness in rule-based classification for data streams. Neurocomputing 265: 127-141 (2017) - [j37]Eyad Elyan, Mohamed Medhat Gaber:
A genetic algorithm approach to optimising random forests applied to class engineered data. Inf. Sci. 384: 220-234 (2017) - [j36]Muhammad Habib Ur Rehman, Prem Prakash Jayaraman, Saif Ur Rehman Malik, Atta ur Rehman Khan, Mohamed Medhat Gaber:
RedEdge: A Novel Architecture for Big Data Processing in Mobile Edge Computing Environments. J. Sens. Actuator Networks 6(3): 17 (2017) - [j35]Mona Nabil Demaidi, Mohamed Medhat Gaber, Nick Filer:
Evaluating the quality of the ontology-based auto-generated questions. Smart Learn. Environ. 4(1): 7 (2017) - [j34]Mohammed M. Abdelsamea, Giorgio Gnecco, Mohamed Medhat Gaber:
A SOM-based Chan-Vese model for unsupervised image segmentation. Soft Comput. 21(8): 2047-2067 (2017) - [c66]Fatima Abdallah, Shadi Basurra, Mohamed Medhat Gaber:
A Hybrid Agent-Based and Probabilistic Model for Fine-Grained Behavioural Energy Waste Simulation. ICTAI 2017: 991-995 - [c65]Ahmed Hussein, Eyad Elyan, Mohamed Medhat Gaber, Chrisina Jayne:
Deep reward shaping from demonstrations. IJCNN 2017: 510-517 - 2016
- [j33]Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Carlos J. Martín-Dancausa, Frederic T. Stahl, João Bártolo Gomes:
A rule dynamics approach to event detection in Twitter with its application to sports and politics. Expert Syst. Appl. 55: 351-360 (2016) - [j32]Zahraa Said Abdallah, Mohamed Medhat Gaber, Bala Srinivasan, Shonali Krishnaswamy:
AnyNovel: detection of novel concepts in evolving data streams. Evol. Syst. 7(2): 73-93 (2016) - [j31]Eyad Elyan, Mohamed Medhat Gaber:
A fine-grained Random Forests using class decomposition: an application to medical diagnosis. Neural Comput. Appl. 27(8): 2279-2288 (2016) - [c64]Ahmed Hussein, Mohamed Medhat Gaber, Eyad Elyan:
Deep Active Learning for Autonomous Navigation. EANN 2016: 3-17 - [c63]Khaled Fawagreh, Mohamed Medhat Gaber, Eyad Elyan:
An Outlier Ranking Tree Selection Approach to Extreme Pruning of Random Forests. EANN 2016: 267-282 - [c62]Thien Le, Frederic T. Stahl, Chris Wrench, Mohamed Medhat Gaber:
A Statistical Learning Method to Fast Generalised Rule Induction Directly from Raw Measurements. ICMLA 2016: 935-938 - [c61]Alfredo Cuzzocrea, Mohamed Medhat Gaber, Staci Lattimer, Giorgio Mario Grasso:
Clustering-Based Spatio-Temporal Analysis of Big Atmospheric Data. ICC 2016 2016: 74:1-74:8 - 2015
- [j30]Mohammed M. Abdelsamea, Giorgio Gnecco, Mohamed Medhat Gaber, Eyad Elyan:
On the Relationship between Variational Level Set-Based and SOM-Based Active Contours. Comput. Intell. Neurosci. 2015: 109029:1-109029:19 (2015) - [j29]Mohammed M. Abdelsamea, Giorgio Gnecco, Mohamed Medhat Gaber:
An efficient Self-Organizing Active Contour model for image segmentation. Neurocomputing 149: 820-835 (2015) - [j28]Zahraa Said Abdallah, Mohamed Medhat Gaber, Bala Srinivasan, Shonali Krishnaswamy:
Adaptive mobile activity recognition system with evolving data streams. Neurocomputing 150: 304-317 (2015) - [j27]Frederic T. Stahl, David May, Hugo Mills, Max Bramer, Mohamed Medhat Gaber:
A Scalable Expressive Ensemble Learning Using Random Prism: A MapReduce Approach. Trans. Large Scale Data Knowl. Centered Syst. 20: 90-107 (2015) - [c60]Alfredo Cuzzocrea, Mohamed Medhat Gaber, Staci Lattimer:
Spatio-temporal analysis of Greenhouse Gas data via clustering techniques. CSCWD 2015: 478-483 - [c59]Alfredo Cuzzocrea, Mohamed Medhat Gaber, Ary Mazharuddin Shiddiqi:
Distributed Classification of Data Streams: An Adaptive Technique. DaWaK 2015: 296-309 - [c58]Khaled Fawagreh, Mohamed Medhat Gaber, Eyad Elyan:
A Replicator Dynamics Approach to Collective Feature Engineering in Random Forests. SGAI Conf. 2015: 25-41 - [c57]Khaled Fawagreh, Mohamed Medhat Gaber, Eyad Elyan:
CLUB-DRF: A Clustering Approach to Extreme Pruning of Random Forests. SGAI Conf. 2015: 59-73 - [e8]Mohamed Medhat Gaber, Mihaela Cocea, Nirmalie Wiratunga, Ayse Göker:
Advances in Social Media Analysis. Studies in Computational Intelligence 602, Springer 2015, ISBN 978-3-319-18457-9 [contents] - [i3]Khaled Fawagreh, Mohamed Medhat Gaber, Eyad Elyan:
On Extreme Pruning of Random Forest Ensembles for Real-time Predictive Applications. CoRR abs/1503.04996 (2015) - [i2]Khaled Fawagreh, Mohamed Medhat Gaber, Eyad Elyan:
An Outlier Detection-based Tree Selection Approach to Extreme Pruning of Random Forests. CoRR abs/1503.05187 (2015) - 2014
- [j26]Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Frederic T. Stahl:
A Survey of Data Mining Techniques for Social Media Analysis. J. Data Min. Digit. Humanit. 2014 (2014) - [j25]Dang-Hoan Tran, Mohamed Medhat Gaber, Kai-Uwe Sattler:
Change detection in streaming data in the era of big data: models and issues. SIGKDD Explor. 16(1): 30-38 (2014) - [j24]João Bártolo Gomes, Mohamed Medhat Gaber, Pedro A. C. Sousa, Ernestina Menasalvas Ruiz:
Mining Recurring Concepts in a Dynamic Feature Space. IEEE Trans. Neural Networks Learn. Syst. 25(1): 95-110 (2014) - [j23]Mohamed Medhat Gaber, João Gama, Shonali Krishnaswamy, João Bártolo Gomes, Frederic T. Stahl:
Data stream mining in ubiquitous environments: state-of-the-art and current directions. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 4(2): 116-138 (2014) - [c56]Joarder Mohammad Mustafa Kamal, M. Manzur Murshed, Mohamed Medhat Gaber:
Progressive Data Stream Mining and Transaction Classification for Workload-Aware Incremental Database Repartitioning. BDC 2014: 8-15 - [c55]Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Carlos J. Martín-Dancausa, Frederic T. Stahl:
Extraction of Unexpected Rules from Twitter Hashtags and its Application to Sport Events. ICMLA 2014: 207-212 - [c54]Safwan Shatnawi, Mohamed Medhat Gaber, Mihaela Cocea:
Automatic Content Related Feedback for MOOCs Based on Course Domain Ontology. IDEAL 2014: 27-35 - [c53]Khaled Fawagreh, Mohamed Medhat Gaber, Eyad Elyan:
Diversified Random Forests Using Random Subspaces. IDEAL 2014: 85-92 - [c52]Alfredo Cuzzocrea, Mohamed Medhat Gaber, Ary Mazharuddin Shiddiqi:
Adaptive data stream mining for wireless sensor networks. IDEAS 2014: 284-287 - [c51]Thien Le, Frederic T. Stahl, João Bártolo Gomes, Mohamed Medhat Gaber, Giuseppe Di Fatta:
Computationally Efficient Rule-Based Classification for Continuous Streaming Data. SGAI Conf. 2014: 21-34 - [c50]Joarder Mohammad Mustafa Kamal, M. Manzur Murshed, Mohamed Medhat Gaber:
Predicting Hot-Spots in Distributed Cloud Databases Using Association Rule Mining. UCC 2014: 800-805 - [c49]Mohammed M. Abdelsamea, Giorgio Gnecco, Mohamed Medhat Gaber:
A Concurrent SOM-Based Chan-Vese Model for Image Segmentation. WSOM 2014: 199-208 - [c48]Mohammed M. Abdelsamea, Giorgio Gnecco, Mohamed Medhat Gaber:
A Survey of SOM-Based Active Contour Models for Image Segmentation. WSOM 2014: 293-302 - [e7]Sherif Sakr, Mohamed Medhat Gaber:
Large Scale and Big Data - Processing and Management. Auerbach Publications 2014, ISBN 978-1-4665-8150-0 [contents] - 2013
- [j22]Mohamed Medhat Gaber, Harinder Singh Atwal:
An entropy-based approach to enhancing Random Forests. Intell. Decis. Technol. 7(4): 319-327 (2013) - [j21]João Bártolo Gomes, Mohamed Medhat Gaber, Pedro A. C. Sousa, Ernestina Menasalvas Ruiz:
Collaborative Data Stream Mining in Ubiquitous Environments using Dynamic Classifier Selection. Int. J. Inf. Technol. Decis. Mak. 12(6): 1287-1308 (2013) - [j20]Mohamed Medhat Gaber, Shonali Krishnaswamy, Brett Gillick, Hasnain AlTaiar, Nicholas Nicoloudis, Jonathan Liono, Arkady B. Zaslavsky:
Interactive self-adaptive clutter-aware visualisation for mobile data mining. J. Comput. Syst. Sci. 79(3): 369-382 (2013) - [j19]Pari Delir Haghighi, Shonali Krishnaswamy, Arkady B. Zaslavsky, Mohamed Medhat Gaber, Abhijat Sinha, Brett Gillick:
Open Mobile Miner: A Toolkit for Building Situation-Aware Data Mining Applications. J. Organ. Comput. Electron. Commer. 23(3): 224-248 (2013) - [j18]Frederic T. Stahl, Bogdan Gabrys, Mohamed Medhat Gaber, Monika Berendsen:
An overview of interactive visual data mining techniques for knowledge discovery. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 3(4): 239-256 (2013) - [c47]Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Frederic T. Stahl:
TRCM: A Methodology for Temporal Analysis of Evolving Concepts in Twitter. ICAISC (2) 2013: 135-145 - [c46]Kieran Jay Edwards, Mohamed Medhat Gaber:
Identifying Uncertain Galaxy Morphologies Using Unsupervised Learning. ICAISC (2) 2013: 146-157 - [c45]João Bártolo Gomes, Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Frederic T. Stahl:
Rule Type Identification Using TRCM for Trend Analysis in Twitter. SGAI Conf. 2013: 273-278 - [c44]Alfredo Cuzzocrea, Shane Leo Francis, Mohamed Medhat Gaber:
An Information-Theoretic Approach for Setting the Optimal Number of Decision Trees in Random Forests. SMC 2013: 1013-1019 - [e6]Mohamed Medhat Gaber, Nirmalie Wiratunga, Ayse Göker, Mihaela Cocea:
Proceedings of the BCS SGAI Workshop on Social Media Analysis 2013 co-located with 33rd Annual International Conference of the British Computer Society's Specialist Group on Artificial Intelligence (BCS SGAI 2013), Cambridge, UK, December 10, 2013. CEUR Workshop Proceedings 1110, CEUR-WS.org 2013 [contents] - [i1]Mariam Adedoyin-Olowe, Mohamed Medhat Gaber, Frederic T. Stahl:
A Survey of Data Mining Techniques for Social Media Analysis. CoRR abs/1312.4617 (2013) - 2012
- [j17]Indre Zliobaite, Albert Bifet, Mohamed Medhat Gaber, Bogdan Gabrys, João Gama, Leandro L. Minku, Katarzyna Musial:
Next challenges for adaptive learning systems. SIGKDD Explor. 14(1): 48-55 (2012) - [j16]Frederic T. Stahl, Mohamed Medhat Gaber, Paul Aldridge, David May, Han Liu, Max Bramer, Philip S. Yu:
Homogeneous and Heterogeneous Distributed Classification for Pocket Data Mining. Trans. Large Scale Data Knowl. Centered Syst. 5: 183-205 (2012) - [j15]Mohamed Medhat Gaber:
Advances in data stream mining. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 2(1): 79-85 (2012) - [c43]Zahraa Said Abdallah, Mohamed Medhat Gaber, Bala Srinivasan, Shonali Krishnaswamy:
CBARS: Cluster Based Classification for Activity Recognition Systems. AMLTA 2012: 82-91 - [c42]João Bártolo Gomes, Shonali Krishnaswamy, Mohamed Medhat Gaber, Pedro A. C. Sousa, Ernestina Menasalvas Ruiz:
Mobile Activity Recognition Using Ubiquitous Data Stream Mining. DaWaK 2012: 130-141 - [c41]Mohamed Bahy Bader-El-Den, Mohamed Medhat Gaber:
GARF: Towards Self-optimised Random Forests. ICONIP (2) 2012: 506-515 - [c40]Zahraa Said Abdallah, Mohamed Medhat Gaber, Bala Srinivasan, Shonali Krishnaswamy:
StreamAR: Incremental and Active Learning with Evolving Sensory Data for Activity Recognition. ICTAI 2012: 1163-1170 - [c39]Ranjani Nagarajan, Alfredo Cuzzocrea, Mohamed Medhat Gaber:
Deploying Mobile Software Agents for Distributed Data Mining on Wireless Sensor Networks: A Comparative Analysis. ICTAI 2012: 1179-1185 - [c38]Alfredo Cuzzocrea, Mohamed Medhat Gaber:
Data Science and Distributed Intelligence: Recent Developments and Future Insights. IDC 2012: 139-147 - [c37]Mohamed Medhat Gaber, Mohamed Bahy Bader-El-Den:
Optimisation of Ensemble Classifiers using Genetic Algorithm. KES 2012: 39-48 - [c36]Daniel Vaccaro-Senna, Mohamed Medhat Gaber:
Incorporating Farthest Neighbours in Instance Space Classification. KES 2012: 345-355 - [c35]Lorraine Chambers, Erik Tromp, Mykola Pechenizkiy, Mohamed Medhat Gaber:
Mobile Sentiment Analysis. KES 2012: 470-479 - [c34]João Bártolo Gomes, Shonali Krishnaswamy, Mohamed Medhat Gaber, Pedro A. C. Sousa, Ernestina Menasalvas Ruiz:
MARS: A Personalised Mobile Activity Recognition System. MDM 2012: 316-319 - [c33]Shonali Krishnaswamy, João Gama, Mohamed Medhat Gaber:
Mobile Data Stream Mining: From Algorithms to Applications. MDM 2012: 360-363 - [c32]Frederic T. Stahl, Mohamed Medhat Gaber, Manuel Martin Salvador:
eRules: A Modular Adaptive Classification Rule Learning Algorithm for Data Streams. SGAI Conf. 2012: 65-78 - [c31]Marwan Hassani, Pascal Spaus, Mohamed Medhat Gaber, Thomas Seidl:
Density-Based Projected Clustering of Data Streams. SUM 2012: 311-324 - [p7]Mohamed Medhat Gaber:
Introduction. Journeys to Data Mining 2012: 1-11 - [e5]Mohamed Medhat Gaber:
Journeys to Data Mining. Springer 2012, ISBN 978-3-642-28046-7 [contents] - [e4]Mohamed Medhat Gaber, Mihaela Cocea, Stephan Weibelzahl, Ernestina Menasalvas, Cyril Labbé:
Proceedings of the 1st International Workshop on Sentiment Discovery from Affective Data, SDAD@ECML/PKDD 2012, Bristol, UK, September 28, 2012. CEUR Workshop Proceedings 917, CEUR-WS.org 2012 [contents] - 2011
- [j14]Suan Khai Chong, Mohamed Medhat Gaber, Shonali Krishnaswamy, Seng Wai Loke:
Energy conservation in wireless sensor networks: a rule-based approach. Knowl. Inf. Syst. 28(3): 579-614 (2011) - [j13]Suan Khai Chong, Mohamed Medhat Gaber, Shonali Krishnaswamy, Seng Wai Loke:
Energy-Aware Data Processing Techniques for Wireless Sensor Networks: A Review. Trans. Large Scale Data Knowl. Centered Syst. 3: 117-137 (2011) - [c30]Zahraa Said Abdallah, Mohamed Medhat Gaber:
KB-CB-N classification: Towards unsupervised approach for supervised learning. CIDM 2011: 283-290 - [c29]Shonali Krishnaswamy, João Gama, Mohamed Medhat Gaber:
Advances in data stream mining for mobile and ubiquitous environments. CIKM 2011: 2607-2608 - [c28]João Bártolo Gomes, Mohamed Medhat Gaber, Pedro A. C. Sousa, Ernestina Menasalvas Ruiz:
Context-Aware Collaborative Data Stream Mining in Ubiquitous Devices. IDA 2011: 22-33 - [c27]Frederic T. Stahl, Mohamed Medhat Gaber, Max Bramer, Philip S. Yu:
Distributed hoeffding trees for pocket data mining. HPCS 2011: 686-692 - [c26]Frederic T. Stahl, Mohamed Medhat Gaber, Han Liu, Max Bramer, Philip S. Yu:
Distributed Classification for Pocket Data Mining. ISMIS 2011: 336-345 - [c25]Hossein Tayebi, Shonali Krishnaswamy, Agustinus Borgy Waluyo, Abhijat Sinha, Mohamed Medhat Gaber:
RA-SAX: Resource-Aware Symbolic Aggregate Approximation for Mobile ECG Analysis. Mobile Data Management (1) 2011: 289-290 - [c24]Abhijat Sinha, Hossein Tayebi, Shonali Krishnaswamy, Agustinus Borgy Waluyo, Mohamed Medhat Gaber:
Resource-aware ECG analysis on mobile devices. SAC 2011: 1012-1013 - [p6]Luke Albert Steller, Shonali Krishnaswamy, Mohamed Medhat Gaber:
Enabling Scalable Semantic Reasoning for Mobile Services. Semantic Services, Interoperability and Web Applications 2011: 178-204 - 2010
- [j12]Varun Chandola, Olufemi A. Omitaomu, Auroop R. Ganguly, Ranga Raju Vatsavai, Nitesh V. Chawla, João Gama, Mohamed Medhat Gaber:
Knowledge discovery from sensor data (SensorKDD). SIGKDD Explor. 12(2): 50-53 (