AUT - Russel Pears

Dr Russel Pears

Senior Lecturer in Computer Science and PhD Programme Leader

Phone: +64 9 921 9999 Ext 5344

Email: russel.pears@aut.ac.nz

Physical Address:
AUT Tower, Level 1,
2 – 14 Wakefield St,
Auckland 1010

Qualifications:

• B.Sc. (Hons.) in Mathematics and Physics, University of Colombo, Sri Lanka
• Postgraduate Diploma in Statistics, University of Sri Jayawardenapura, Sri Lanka
• M.Sc. in Computer Science, University of Wales, College of Cardiff, United Kingdom
• Ph.D. in Computer Science, University of Wales, College of Cardiff, United Kingdom

Biography:

Russel’s career in Computing spans 27 years. During this time he has held a number of academic positions in Universities both here and overseas. He has taught in various topics in Computer Science while practicing as a consultant in the IT industry in the areas of Database  Systems and Data Mining.  In his role as PhD Programme Leader Russel provides advice to prospective PhD students and guides students in the production of a credible research proposal.

Teaching Areas:

• Data Mining
• Database Systems
• Research Methods

Postgraduate Supervision
I have supervised 12 thesis/dissertation students to completion at the Masters level, and 1 student at the PhD level.

Research areas:

My research interests are currently in three areas: Mining High Speed Data Streams Pattern Mining and Time Series Prediction.

Publications:

a.  Journal Publications

• Usman M, and Pears R, “Integration of Data Mining and Data Warehousing: A Practical Methodology for Integration of Data Mining and Data Warehousing: A Practical Methodology”, accepted for publication in International Journal of Advancements in Computing Technology, 2010.
• Connor A, Limbu D, McDonell S and Pears R, “Improving Web Information Retrieval using Shared Contexts” accepted for publication in 2010 in the International Journal of Information Sciences and Computer Engineering.
• Widiputra H, Pears R, Serguieva A and Kasabov N, “Dynamic Interaction Networks in Modelling and Predicting the Behaviour of Multiple Interactive Stock Markets”, Journal of Intelligent System in Accounting, Finance and Management, 16(1), 2009.
• Pears R, Houliston B, “Optimization of multidimensional aggregates in data warehouses”, Journal of Database Management, 18(1), 2007.

b.  Book Chapters

• Widiputra H, Pears R, Kasabov N, “Kalman Filter to Estimate Dynamic and Important Patterns of Interaction between Multiple Variables” In Mark Columbus (ed.), Kalman Filtering, Nove Science, New York, 2010.
• Pears R and Otema, R, “Boosting Prediction Accuracy of Imbalanced Data in Financial Credit Applications” In Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection, IGI Global Publishing, 2009.
• Pears R, Houliston B, “Accelerating Multi Dimensional Queries in Data Warehouses” In Keng Siau and John Erickson (eds), Advanced Principles for Improving Database Design, System Modelling, and Software Development, IGI Global Publishing, USA., 2008.
• Koh Yun Sing and Pears R, “A Multi Methodological Approach to Rare Association Rule Mining”, accepted for publication in Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection, IGI Global Publishing, 2008.
• Kasabov N, Song Q, Jain, V, Benuskova, L, Gottgtroy, P, Jain, V, Verma, A, Havukkala, I, Rush, E, Pears, R, Tjahjana, A, Hu, Y, MacDonell, S,” Integrating local and personalised modelling with global ontology knowledge bases for biomedical and bioinformatics decision support”. In: Comp. Intel. In Biomed. & Bioinform., SCI 151, T.G. Smolinski et al. (eds), Springer-Verlag, Berlin Heidelberg, 2007

c.  Refereed Conference Publications

• Koh Y, and Pears R, ”Valency based Weighted Association Rule Mining” accepted for publication at the 14th Pacific-Asia Conference Knowledge Discovery and Data Mining, PAKDD 2010.
• Hoeglinger S, Pears R, “CBDT: A Concept Based Data Stream Miner”. In: T Theerramunkong, B Kijsirikul, N Cercone N and T B Ho (Eds.): PAKDD 2009: Advances in Knowledge Discovery and Data Mining, 13th Pacific-Asia Conference, 2009.
• Koh Y, Pears R, "Non-Redundant Rare Itemset Generation", Proceedings of the 2009 Australasian Data Mining Conference, 2009, Melbourne, Australia.
• Widiputra H, Pears R, and Kasbov N, “A Novel Evolving Clustering Algorithm with Polynomial Regression for Chaotic Time-Series Prediction”, Proceedings of the 16th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly, 2009.
• Limbu D, Connor A, Pears R and MacDonell S, “Improving Web Search Using Contextual Retrieval”, Proceedings of the 2009 Sixth International Conference on Information Technology: New Generations, Las Vegas, 2009.
• Koh Y, Pears R, “Transaction Clustering Using a Seeds Based Approach”, In Takashi Washio, Einoshin Suzuki, Kai Ming Ting, Akihiro Inokuchi (Eds.): Advances in Knowledge Discovery and Data Mining, 12th Pacific-Asia Conference, PAKDD 2008, Osaka, Japan.
• Widiputra H, Pears R, Kasbov N, "Personalised Modelling for Multiple Time-Series Data Prediction", 15th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Assembly, 2008.
• Shankaranayanan, A, Amaldas C, Pears R, “Blast those sequences: A Gridified Framework for Bioinformatics Blast using the A3pviGrid”, BIOTECHNO 2008, International Conference on Biocomputation, Bioinformatics, and Biomedical Technologies, Rumania, June 2008.
• Koh Y, Pears R, “Rare Association Rule Mining via Transaction Clustering”, Proceeding of the 2008 Australasian Data Mining Conference, 2008, Hobart, Australia.
• Koh Y, Pears R,” Efficiently finding negative association rules without support”, In AI 2007: Advances in Artificial Intelligence, 4830/2007, 710-714, Berlin.
• Pears R, Kutty S, “FGC: An efficient Constraint Based Frequent Set Miner”, Proceedings of the 2007 ACS/IEEE International Conference on Computer Systems and Applications, AICCSA, 2007.
• Hoeglinger S, Pears R, “Use of Hoeffding trees in concept based data stream mining”, Proceedings of the 2007 Third International Conference on Information and Automation for Sustainability ICIAFs 2007, Melbourne, Australia.
• Pears R, Ee J, “Searching genomic databases using the prime factor filter”, Sustainable Development through Effective man-machine co-existence, IEEE 2nd International Conference on Information and Automation (ICIA 2006), Colombo, Sri Lanka.
• Limbu D, Connor A, Pears R, MacDonell S,” Contextual relevance feedback in web information retrieval”, The 1st International Symposium in Information Interaction in Context (IIiX) [Proceedings], 2006, Copenhagen, Denmark.
• Limbu D, Pears R, Connor A,  MacDonell S, “ Contextual and concept-based interactive query expansion, Preparing for the Future - Capitilising on IT: Proceedings of the 19th Annual Conference of the National Advisory Committee on Computing Qualifications, 151-156, Wellington, New Zealand, 2006.
• Pears R, Gottgtroy P, Petrova K, Macdonell S, “Research and development report: data mining - Phase 1” (A confidential report)  produced for MediaLab, Lucent International, Lucent New Zealand and Telecom New Zealand, 2006.