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T. Hoang, J. Lawall, Y. Tian, R. J. Oentaryo, and D. Lo, "PatchNet: Hierarchical deep learning-based stable patch identification for the Linux kernel,'' IEEE Transactions on Software Engineering (IEEE-TSE), vol. 47, pp. 2471-2486, 2021. [Paper][DOI]
T. Hoang, R. J. Oentaryo, T.-D. B. Le, and D. Lo, "Network-clustered multi-modal bug localization," IEEE Transactions on Software Engineering (IEEE-TSE), vol. 45, no. 10, pp. 1002-1023, 2019. [Paper][DOI]
R. J. Oentaryo, E.-P. Lim, X. J. S. Ashok, P. K. Prasetyo, K. H. Ong, and Z. Q Lau, "Talent flow analytics in online professional network," Data Science and Engineering (DSE), vol. 3, no. 3, pp. 199-220, 2018. [Paper][DOI][Demo]
F. Thung, R. J. Oentaryo, D. Lo, and Y. Tian, "WebAPIRec: Recommending web APIs to software projects via personalized ranking," IEEE Transactions on Emerging Topics in Computational Intelligence (IEEE-TETCI), vol. 1, no. 3, pp. 145-156, 2017. [Paper][DOI]
T. V. Le, R. J. Oentaryo, S. Liu, and H. C. Lau, "Local Gaussian processes for efficient fine-grained traffic speed prediction," IEEE Transactions on Big Data (IEEE-TBD), vol. 3, no. 2, pp. 194-207, 2017. [Paper][DOI]
A. J. Torabi, M. J. Er, X. Li, B. S. Lim, L.-Y. Zhai, R. J. Oentaryo, G. O. Peen, and J. M. Zurada, "A survey on artificial intelligence-based modeling techniques for high speed milling processes," IEEE Systems Journal (IEEE-SYSTJ), vol. 9, no. 3, pp. 1069-1080, 2015. [Paper][DOI]
R. J. Oentaryo, E.-P. Lim, M. Finegold, D. Lo, F.-D. Zhu, C. Phua, E.-Y. Cheu, G.-E. Yap, K. Sim, M. N. Nguyen, K. Perera, B. Neupane, M. Faisal, Z.-Y. Aung, W. L. Woon, W. Chen, D. Patel, and D. Berrar, "Detecting click fraud in online advertising: A data mining approach," Journal of Machine Learning Research (JMLR), vol. 15, pp. 99-140, 2014. [Paper][Dataset][Video]
R. J. Oentaryo, M. J. Er, S. Linn, and X. Li, "Online probabilistic learning for fuzzy inference systems," Expert Systems with Applications (ESWA), vol. 41, no. 11, pp. 5082-5096, 2014. [Paper][DOI]
M. Pratama, M. J. Er, X. Li, R. J. Oentaryo, E. Lughofer, and I. Arifin, "Data driven modeling based on dynamic parsimonious fuzzy neural network," Neurocomputing (NEUCOM), vol. 110, pp. 18-28, 2013. [Paper][DOI]
R. J. Oentaryo, M. Pasquier, and C. Quek, "RFCMAC: A novel reduced localized neuro-fuzzy system approach to knowledge extraction," Expert Systems with Applications (ESWA), vol. 38, no. 10, pp. 12066-12084, 2011. [Paper][DOI]
R. J. Oentaryo and M. Pasquier, "Knowledge consolidation and inference in the integrated neuro-cognitive architecture," IEEE Intelligent Systems (IEEE-MIS), vol. 26, no. 4, pp. 62-71, 2011. [Paper][DOI]
M. J. Er and R. J. Oentaryo, "Book review - Computational intelligence: Methods and techniques," IEEE Computational Intelligence Magazine (IEEE-CIM), vol. 6, no. 4, pp. 76-78, 2011. [Paper][DOI]
R. J. Oentaryo, M. Pasquier, and C. Quek, "GenSoFNN-Yager: A novel brain-inspired neuro-fuzzy decision support system realizing Yager inference," Expert Systems with Applications (ESWA), vol. 35, no. 4, pp. 1825-1840, 2008. [Paper][DOI]
M. Pasquier and R. J. Oentaryo, "Learning to drive the human way: A step towards intelligent vehicles," International Journal of Vehicle Autonomous Systems (IJVAS), vol. 6, no. 1-2, pp. 24-47, 2008. [Paper][DOI]
R. K.-W. Lee, T. Hoang, R. J. Oentaryo, and D. Lo, "Keen2Act: Activity Recommendation in Online Social Collaborative Platforms,'' in Proceedings of the ACM Conference on User Modeling, Adaptation and Personalization (UMAP), Genoa, Italy, 2020. [Paper][DOI]
T. Hoang, J. Lawall, R. J. Oentaryo, Y. Tian, and D. Lo, "PatchNet: A tool for deep patch classification," in Proceedings of the International Conference on Software Engineering (ICSE), Montreal, Canada, 2019, pp. 83-86. [Paper][DOI][Demo]
R. J. Oentaryo, X. J. S. Ashok, E.-P. Lim, and P. K. Prasetyo, "JobComposer: Career path optimization via multicriteria utility learning," in Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases Workshop (ECML-PKDDW), Dublin, Ireland, 2018. [Paper]
R. J. Oentaryo, X. J. S. Ashok, E.-P. Lim, and P. K. Prasetyo, "On analyzing job hop behavior and talent flow networks," in Proceedings of the International Conference on Data Mining Workshop (ICDMW), New Orleans, 2017, pp. 207-214. [Paper][DOI] (Acceptance: 31.25%)
R. J. Oentaryo, A. Murdopo, P. K. Prasetyo, and E.-P. Lim, "On profiling bots in social media," in Proceedings of the International Conference on Social Informatics (SocInfo), Bellevue, WA, 2016, pp. 92-109. [Paper][DOI] (Acceptance: 28%; Full paper)
V. Lai, K. J. Shim, R. J. Oentaryo, P. K. Prasetyo, C. Vu, E.-P. Lim, and D. Lo, " CareerMapper: An automated resume evaluation tool," in Proceedings of the IEEE International Conference on Big Data (IEEE BigData), Washington, DC, 2016, pp. 4005-4007. [Paper][DOI] (Poster paper)
J. Lin, R. J. Oentaryo, E.-P. Lim, C. Vu, A. Vu, and A. T. Kwee, "Where is the goldmine? Finding promising business locations through Facebook data analytics," in Proceedings of the ACM Conference on Hypertext and Social Media (HT), Halifax, Canada, 2016, pp. 93-102. [Paper][DOI][Demo] (Acceptance: 22%; Full paper)
J. Lin, R. J. Oentaryo, E.-P. Lim, C. Vu, A. Vu, A. T. Kwee, and P. K. Prasetyo, "A business zone recommender system based on Facebook and urban planning data," in Proceedings of the European Conference on Information Retrieval (ECIR), Padova, Italy, 2016, pp. 641-647. [Paper][DOI] (Acceptance: 30%; Poster paper)
R. J. Oentaryo, S. D. Handoko, and H. C. Lau, "Algorithm selection via ranking," in Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Austin, TX, 2015, pp. 1826-1832. [Paper] (Acceptance: 26%; Full paper)
R. J. Oentaryo, J.-W. Low, and E.-P. Lim, "Chalk and cheese in Twitter: Discriminating personal and organization accounts," in Proceedings of the European Conference on Information Retrieval (ECIR), Vienna, Austria, 2015, pp. 465-476. [Paper][DOI] (Acceptance: 23%; Full paper)
R. J. Oentaryo, J.-W. Low, A. Murdopo, P. K. Prasetyo, and E.-P. Lim, "Characterizing bots and humans in social media," in Proceedings of the International Conference on Computational Social Science (IC2S2), Helsinki, Finland, 2015. [Paper] (Acceptance: 34%; Short paper)
T.-D. B. Le, R. J. Oentaryo, and D. Lo, "Information retrieval and spectrum based bug localization: Better together," in Proceedings of the Joint Meeting of the European Software Engineering Conference and the ACM SIGSOFT Symposium on the Foundations of Software Engineering (ESEC/FSE), Bergamo, Italy, 2015, pp. 882-893. [Paper][DOI] (Acceptance: 25%; Full paper)
R. J. Oentaryo, E.-P. Lim, J.-W. Low, D. Lo, and M. Finegold, "Predicting response in mobile advertising with hierarchical importance-aware factorization machine," in Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM), New York, NY, 2014, pp. 123-132. [Paper][DOI] (Acceptance: 18%; Full paper)
F. C. T. Chua, R. J. Oentaryo, and E.-P. Lim, "Modeling temporal adoptions using dynamic matrix factorization," in Proceedings of the IEEE International Conference on Data Mining (ICDM), Dallas, TX, 2013, pp. 91-100. [Paper][DOI] (Acceptance: 19%; Full paper)
R. J. Oentaryo and E.-P. Lim, "Mining fraudulent patterns in online advertising," First International Network on Trust, Workshop on Trust Within and Between Organizations (FINT), Singapore, 2013. [Paper]
R. J. Oentaryo, E.-P. Lim, D. Lo, F.-D. Zhu, and P. K. Prasetyo, "Collective churn prediction in social networks," in Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Istanbul, Turkey, 2012, pp. 210-214. [Paper][DOI] (Acceptance: 25%; Short paper)
R. J. Oentaryo, M. J. Er, L. San, L.-Y. Zhai, and X. Li, "Bayesian ART-based fuzzy inference system: A new approach to prognosis of machining processes," in Proceedings of the IEEE International Conference on Prognostics and Health Management (PHM), Denver, Colorado, 2011, pp. 1-10. [Paper][DOI]
M. Pratama, M. J. Er, X. Li, L. San, R. J. Oentaryo, L.-Y. Zhai, A. J. Torabi, and I. Arifin, "Genetic dynamic fuzzy neural network (GDFNN) for nonlinear system identification," in Proceedings of the IEEE International Symposium on Neural Networks (ISNN), Guilin, China, 2011, vol. 6676, pp. 525-534. [Paper][DOI]
M. Pratama, M. J. Er, X. Li, O. P. Gan, R. J. Oentaryo, L. San, L.-Y. Zhai, and I. Arifin, "Tool wear prediction using evolutionary dynamic fuzzy neural network (EDFNN)", in Proceedings of the Annual Conference on IEEE Industrial Electronics Society (IECON), Melbourne, Australia, 2011, pp. 4739-4744. [Paper][DOI]
R. J. Oentaryo and M. Pasquier, "A novel dual neuro-fuzzy system approach for large-scale knowledge consolidation," in Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Jeju, Korea, 2009, pp. 53-58. [Paper][DOI]
D. Ko, R. J. Oentaryo, and M. Pasquier, "An adaptive history network method to improve the genetic optimization of pattern recognition systems," in Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Jeju, Korea, 2009, pp. 23-28. [Paper][DOI]
R. J. Oentaryo and M. Pasquier, "Towards a novel integrated neuro-cognitive architecture (INCA)," in Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), Hong Kong, China, 2008, pp. 1902-1909. [Paper][DOI]
R. J. Oentaryo and M. Pasquier, "A reduced rule-based localist network for data comprehension," in Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), Hong Kong, China, 2008, pp. 2660-2667. [Paper][DOI]
W. Duch, R. J. Oentaryo, and M. Pasquier, "Cognitive architectures: Where do we go from here?," in Frontiers in Artificial Intelligence and Applications, P. Wang, B. Goertzel, and S. Franklin, Eds.: IOS Press, 2008, vol. 171, pp. 122-136. [Paper][Transcript][DOI] (Popular)
E. Lumanpauw, M. Pasquier, and R. J. Oentaryo, "Generic GA-based meta-level parameter optimization for pattern recognition systems," in Proceedings of the IEEE Congress on Evolutionary Computation (CEC), Singapore, 2007, pp. 1593-1600. [Paper][DOI]
R. J. Oentaryo and M. Pasquier, "GenSoFNN-Yager: A novel hippocampus-like learning memory system realizing Yager inference," in Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, Canada, 2006, pp. 705-712. [Paper][DOI]
R. J. Oentaryo and M. Pasquier, "Self-trained automated parking system," in Proceedings of the IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV), Kunming, China, 2004, vol. 2, pp. 1005-1010. [Paper][DOI]
R. J. Oentaryo, "Knowledge consolidation and inference in an integrated neuro-cognitive architecture," School of Computer Engineering, Nanyang Technological University, Singapore, Doctoral Dissertation, 2011. [Thesis]
R. J. Oentaryo, "Automated driving based on self organizing GenSoYager neuro-fuzzy system," School of Computer Engineering, Nanyang Technological University, Singapore, Final Year Project Dissertation (Technical Report C2i-TR-002/05), 2004. [Thesis] (Award: ITMA Gold Medal cum Book Prize)