Position/s

Dean of School
School of Computer Science, Engineering and Mathematics

SACITT Professor of Computer Science
School of Computer Science, Engineering and Mathematics

Dean of Engineering
School of Computer Science, Engineering and Mathematics

Dean of Information and Communication Technology
School of Computer Science, Engineering and Mathematics

Biography

Professor John Roddick joined Flinders in April 2000 after 15 years at the Universities of Tasmania and South Australia (where he was Head of the School of Computer and Information Science for 4 years). This followed 10 years experience in the computing industry as (progressively) a programmer, analyst, project leader and consultant. He became Dean of the School in January 2008 and was reappointed to that role at the start of 2012. He is also Deputy Executive Dean for the Faculty of Science and Engineering.

Qualifications

PhD, La Trobe
MSc, Deakin University
BSc(Eng)(Hons), Imperial College, London

Honours, awards and grants

Professor Roddick is a Fellow of the Institute of Engineers, Australia (FIEAust) and a Fellow of the Australian Computing Society (FACS).

Selected Grants since 2002

  1. Roddick, J.F. Techniques for active conceptual modelling and guided data mining for rapid knowledge discovery. ARC Linkage. $223,000 (ARC and rL-Solutions). 2011/13.
  2. Bull, M.J., Roddick, J.F. and Sih, A. Behavioural syndromes and social networks in sleepy lizards. ARC Discovery. $375,000. 2010/12.
  3. Roddick, J.F., Ceglar, A. and de Vries, D. Detection of Anomalies in Transaction Sequences (DATS) Project, DSTO. $269,000. 2005-8.
  4. Roddick, J.F. and Calder P.R. Managing and Mining Evolving Ontologies through combining Patterns Languages and Data Mining, ARC Linkage with RACS and ACS. $196,500 (ARC and Partners). 2006-2008.
  5. McIntyre, J, Roche, A., Roddick, J.F. Morgan, DL and Metcalfe, M. Addressing Indigenous complex health, housing and social inclusion issues through critical systems approaches to build workforce capacity, ARC Linkage Grant with SA Department of Human Services and Neporendi Aboriginal Forum Inc., $96,444 (ARC and Partners), 2005-2007.
  6. Roddick, J.F., et al. Improving Australia's Data Mining and Knowledge Discovery Research ARC Research Network Funding Grant, $20,000 2004.
  7. Clarke, S.R., Matisons, J., Downing, A. and Roddick, J.F. Strategic Business Principles for the Economic Development of New Technologies in Regional Areas. $103,168 (ARC and Partners), 2004-2006.
  8. Roddick, J.F., Data Mining for Defence Information Analysis, LongARM Project, DSTO, $30,000 2004.
  9. Roddick, J.F., with Power-Solutions Inc. Power Knowledge Builder Project, START Grant, $1,100,000, 2004-2006.
  10. Holledge, J.F., Roddick, J.F., Hartog, J, et al. AusStage: Australian Performing Arts Gateway, Phase Two - Enhancement and Information Retrieval. ARC LIEF Grant, $280,000 2003.
  11. Roddick, J.F. et al, Analysis of Pathology Ordering by GPs, $122,000 (DHAC), 2002.
  12. Roddick, J.F. Employing Summarisation and Induction Techniques to Improve User Responsiveness in Database Applications. ARC SPIRT Grant with HP Labs, $101,846 (ARC and Compaq), 2001-2003.

Key responsibilities

He is currently the SACITT Chair in Computer Science and Dean of the School of Computer Science, Engineering and Mathematics at Flinders University. He is also Dean of Engineering and Dean of ICT for Flinders University.

Topic Coordinator:

Topic Lecturer:

  • ENGR1401  Professional Skills for Engineers
  • ENGR4742  Standards, Ethics and Compliance

Research expertise

  • Artificial intelligence and image processing
  • Information systems

Research interests

Prof. Roddick's research specialises in the fields of:

  • Data Mining and Knowledge Discovery - specifically in temporal and spatial data mining and as applied to medical and health data, and to defence and security;
  • Conceptual Modelling - the development of conceptual models for complex systems and the manner in which these models can be used to build data-oriented solutions to difficult problems.

Since the late 1980s Professor Roddick has contributed to the area of conceptual modelling and intelligent databases including the development of techniques for data summarization, spatio-temporal databases, query languages, evolution and change in data and metadata management, information semantics and, data mining and knowledge discovery.

His papers in these areas have received around 4,800 citations (per Google Scholar) with eleven with over 100 citations.  He has an h-index of 30.

His work has resulted in contributions to the design and development of database architectures, query languages and systems that enable the semantics inherent in data to be more readily understood and manipulated, thus enabling systems to adapt.  Part of his work in temporal query languages, for example, contributed to the TSQL2 temporal language proposal.  His research agenda has a particular focus on complex and large volumes of data, commonly using medical data as the application domain.

Professor Roddick has published widely, including a number of well-cited surveys.  He maintains active collaborative links with a number of researchers internationally, and has undertaken commercial research contracts with a number of organisations in his area of expertise including the Defence Science and Technology Organisation (DSTO), the Royal Australasian College of Surgery, EDS Australia, PriceWaterhouseCoopers, the SA Government, rL Solutions and PowerHealth Solutions.

Supervisory interests

  • Data mining and knowledge discovery
  • Data semantics
  • Database modelling

RHD research supervision

Current

Principal supervisor : Computer Science (3) ;

Completion

Principal supervisor : Computer Science (12) ;

Publications

  • Tang, L., Pan, J., Guo, X., Chu, S. and Roddick, J. (2014). A Novel Approach on Behavior of Sleepy Lizards Based on K-Nearest Neighbor Algorithm. In Witold Pedrycz, Shyi-Ming Chen, ed. Social Networks: A Framework of Computational Intelligence. Switzerland: Springer, pp. 287-311.
    [Web Link]
  • Ceglar, A.J., Morrall, R. and Roddick, J.F. (2010). Mining Medical Administrative Data - The PKB Suite. In Carlos Soares and Rayid Ghani, ed. Data Mining for Business Applications, Frontiers in Artificial Intelligence and Applications. Netherlands: IOS Press, pp. 110-119.
  • Roddick, J.F. (2009). Schema evolution. In Ling Liu, M. Tamer Ozsu, ed. Encyclopedia of database systems. New York, USA: Springer, pp. 2479-2481.
    [10.1007/978-0-387-39940-9_1532]
  • Roddick, J.F. (2009). Schema versioning. In Ling Liu, M. Tamer Ozsu, ed. Encyclopedia of database systems. New York: Springer, pp. 2499-2502.
    [10.1007/978-0-387-39940-9_323]
  • Roddick, J.F. and Toman, D. (2009). Temporal vacuuming. In Ling Liu, M. Tamer Ozsu, ed. Encyclopedia of database systems. New York: Springer, pp. 3023-3027.
    [10.1007/978-0-387-39940-9_1045]
  • Wahlstrom, K., Roddick, J.F., Sarre, W., Estivill-Castro, V. and de Vries, D.B. (2009). Legal and technical issues of privacy preservation in data mining. In John Wang, ed. Encyclopedia of Data Warehousing and Mining. 2nd ed. Hershey, PA, USA: Information Science Reference, pp. 1158-1163.
    [Web Link]
  • Roddick, J.F., Ceglar, A.J., de Vries, D.B. and La-Ongsri, S. (2007). Postponing schema definition: Low Instance-to-Entity Ratio (LItER) modelling. In Peter P Chen and Leah Y Wong, ed. Active Conceptual Modeling of Learning. Berlin: Springer, pp. 206-216.
    [10.1007/978-3-540-77503-4_16]
  • Mooney, C.H., de Vries, D.B. and Roddick, J.F. (2006). A multi-level framework for the analysis of sequential data. In Graham J. Williams and Simeon J. Simoff, ed. Data Mining: Theory, Methodology, Techniques and Applications. Heidelberg, Germany: Springer, pp. 229-243.
  • Chu, S., Shieh, C. and Roddick, J.F. (2004). A tutorial on meta-heuristics for optimization. In Jeng-Shyang Pan, Hsiang-Cheh Huang and Lakhmi C. Jain, ed. INTELLIGENT WATERMARKING TECHNIQUES. Singapore: World Scientific Publishing, pp. 97-132.
  • Ceglar, A.J., Roddick, J.F. and Calder, P.R. (2003). Guiding knowledge discovery through interactive data mining. In Pendharkar, Parag, ed. Managing Data Mining Technologies in Organisations: Techniques and Applications. Hershey, USA: Idea Group Publishing, pp. 45-87.
  • Roddick, J.F. and Lees, B. (2001). Paradigms for Spatial and Spatio-Temporal Data Mining. In Geographic Data Mining and Knowledge Discovery. London, UK: Taylor and Francis, pp. 33-49.
  • Roddick, J.F. and Wahlstrom, K. (2001). On the Impact of Knowledge Discovery and Data Mining. In Computer Ethics 2000. Adelaide, SA: Australian Computer Society, pp. 147-163.
  • Roddick, J.F., Hornsby, K. and Spiliopoulou, M. (2001). An Updated Bibliography of Temporal, Spatial and Spatio-Temporal Data Mining. In Temporal, Spatial and Spatio-Temporal Data Mining. Berlin, Germany: Springer, pp. 147-163.
  • Roddick, J.F. (2014). Ontologies in Data Management and Data Mining - Keynote Address. In 27th International Conference on Industrial Engineering and other Applications of Applied Intelligent Systems (IEA-AIE2014) 27th International Conference on Industrial Engineering and other Applications of Applied Intelligent Systems (IEA-AIE2014) Kaohsiung, Taiwan. Jun 2014.
  • Roddick, J.F. (2009). Pattern specification and discovery in higher order data mining. In Bin-Yih Liao, Jeng-Shyang Pan, Peng Shi and Chin-Shiuh Shieh, ed. Proceedings fourth international conference on innovative computing, information and control. Institute of Electrical and Electronics Engineers ( IEEE ). Fourth International Conference on Innovative Computing, Information and Control (ICICIC2009) Kaohsiung, Taiwan. Dec 2009.
    [Web Link]
  • Chu, S., Roddick, J.F. and Chen, T. (2002). A genetic clustering algorithm for mean-residual vector quantization. In ICAST 2002: proceedings of the 18th International Conference on Advanced Science and Technology. Chicago, USA: Mid-America Chinese American Professionals Association. 18th International Conference on Advanced Science and Technology. Chicago, USA, pp. 91-99.
  • Warren, J., Roddick, J.F., Webb, G. and Williams, G. (2006). Guest Editor's Introduction to Special Issue on Health Data Mining. Ejournal of Health Informatics, 1(1)
    [Web Link]
  • Roddick, J.F., Fule, P. and Graco, W.J. (2003). Exploratory medical knowledge discovery: experiences and issues. Sigkdd Explorations, 5(1) pp. 94-99.
    [10.1145/959242.959243]
  • Roddick, J.F. and Rice, S. (2001). What's Interesting About Cricket? - On Thresholds and Anticipation in Discovered Rules. Sigkdd Explorations, 3(1) pp. 1-5.
  • Brankovic, L., Coddington, P., Roddick, J.F., Steketee, C., Warren, J. and Wendelborn, A. (2007). Conference Proceedings editor. Proceedings of the fifth Australasian symposium on ACSW frontiers. Ballarat, VIC: Conferences in Research and Practice in Information Technology (CRPIT). 68 pp. 1-247.
  • Grundy, J.J., Hartmann, S., Laender, A., Maciazek, L. and Roddick, J.F. (2007). Conference Editor. Challenges in conceptual modelling - Tutorials, posters, panels and industrial contributions at the 26th International conference on Conceptual Modelling - ER 2007. Auckland, New Zealand: Conferences in Research and Practice in Information Technology (CRPIT). 83
  • Roddick, J.F. and Hinze, A. (2007). Conference Editor. Conceptual Modelling 2007: Proceedings of the Fourth Asia-Pacific Conference on Conceptual Modelling (APCCM2007) Ballarat, VIC: Conferences in Research and Practice in Information Technology (CRPIT). 67
  • Roddick, J.F., Benjamins, R., Si-Said Cherfi, S., Chiang, R., Elmasri, R., Grandi, F., et al. (2006). Editors. Advances in Conceptual Modeling: Theory and Practice. Germany: Springer.
  • Rampersad, G.C., Roddick, J. and Salier, M. (2014). Building effective innovation clusters: An Australian Case Study of Tonsley. In Advances in Management Engineering and Information Technology. International Conference on Advances in Management Engineering and Information Technology (AMEIT2014) Hong Kong. Sep 2014.
  • Cheng, P., Chu, S., Lin, C. and Roddick, J. (2014). Distortion-Based Heuristic Sensitive Rule Hiding Method - The Greedy Way. In LNAI 8481-Modern Advances in Applied Intelligence (IEA/AIE 2014) Springer-Verlag. The 27th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014. Kaohsiung, Taiwan. Jun 2014, pp. 77-86.
    [10.1007/978-3-319-07455-9]
  • Liang, P. and Roddick, J.F. (2014). RPL: A Ruleset Pattern Language. In Artificial Intelligence and Industrial Application. WIT Press. International Conference on Artificial Intelligence and Industrial Applicatio (AIIA2014) Shatin, Hong Kong. Sep 2014.
  • Roddick, J.F. and La-Ongsri, S. (2014). Towards Polymorphic Relationships in the Entity-Relationship Model. In Computer Science and Systems Engineering. WIT Press. International Conference on Computer Science and Systems Engineering (CSSE2014) Shatin, Hong Kong. Sep 2014.
  • Liang, P., Roddick, J.F. and de Vries, D. (2013). Searching Frequent Pattern and Prefix Trees for Higher Order Rules. In Peter Christen, Paul Kennedy, Lin Liu, Kok-Leong Ong, Andrew Stranieri and Yanchang Zhao, ed. Eleventh Australasian Data Mining Conference: AusDM 2013. CRPIT. Eleventh Australasian Data Mining Conference: AusDM 2013. Canberra. Nov 2013.
    [Web Link]
  • Shih, H., Chu, S., Roddick, J.F., Ho, J., Liao, B. and Pan, J. (2013). A Reduce Identical Event Transmission Algorithm Using in Wireless Sensor Network. In M Kudelka, J Pokorný, V Snášel & A Abraham, ed. Proceedings of the Third International Conference on Intelligent Human Computer Interaction. Prague, Czech Republic: Springer. 3rd International Conference on Intelligent Human Computer Interaction. Prague, Czech Republic. Aug 2011, pp. 147-154.
    [10.1007/978-3-642-31603-6_13]
  • Guo, X., Chu, S., Tang, L., Roddick, J. and Pan, J. (2012). A Research on Behavior of Sleepy Lizards Based on KNN Algorithm. In J-S Pan, S-M Chen and NT Nguyen, ed. Intelligent Information and Database Systems (ACIIDS 2012) Proceedings. Heidelberg, Germany: Springer-Verlag. 4th Asian Conference. Kaohsiung, Taiwan. Mar 2012, pp. 109-118.
    [10.1007/978-3-642-28490-8_12]
  • Yan, L., Chu, S., Roddick, J. and Pan, J. (2012). Directional Discriminant Analysis Based on Nearest Feature Line. In J-S Pan, S-M Chen & NT Nguyen, ed. Intelligent Information and Database Systems (ACIIDS 2012) Proceedings. Heidelberg, Germany: Springer-Verlag. 4th Asian Conference. Kaohsiung, Taiwan. Mar 2012, pp. 119-128.
    [10.1007/978-3-642-28490-8_13]
  • Li, R., de Vries, D. and Roddick, J.F. (2011). Bands of Privacy Preserving Objectives: Classification of PPDM Strategies. In Peter Vamplew, Andrew Stranieri, Kok-Leong Ong, Peter Christen and Paul Kennedy, ed. Data Mining and Analytics 2011. Ballarat, Australia: Conferences in Research and Practice in Information Technology (CRPIT). Ninth Australasian Data Mining Conference (AusDM 2011) Ballarat, Australia. Dec 2011, pp. 137-152.
  • Chu, S., Hsiang-Cheh, H., Roddick, J.F. and Pan, J. (2011). Overview of Algorithms for Swarm Intelligence. In Computational Collective Intelligence: Technologies and Applications. Berlin: Springer. 3rd International Conference, ICCCI 2011. Gdynia, Poland. Sep 2011, pp. 28-41.
  • Bu, S., Chu, S., Liu, X. and Roddick, J. (2011). Image Recognition Based on Kernel Self-optimized Learning. In Proceedings of the 2nd International Conference on Innovations in Bio-inspired Computing and Applications. Online: IEEE Computer Society. 2nd International Conference on Innovations in Bio-inspired Computing and Applications. ShenZhen, China. Dec 2011, pp. 73-76.
  • Sun, C., Zeng, J., Chu, S., Roddick, J. and Pan, J. (2011). Solving Constrained Optimization Problems by an Improved Particle Swarm Optimization. In Proceedings of IBICA 2011. IEEE. 2nd International Conference on Innovations in Bio-inspired Computing and Applications. ShenZhen, China. Dec 2011, pp. 124-128.
    [Web Link]
  • Yan, L., Chu, S., Pan, J. and Roddick, J. (2011). Neighborhood Discriminant Nearest Feature Line Analysis for Face Recognition. In Proceedings of the 2nd International Conference on Innovations in Bio-inspired Computing and Applications. IEEE Computer Society. 2nd International Conference on Innovations in Bio-inspired Computing and Applications. ShenZhen, China. Dec 2011, pp. 344-347.
    [10.1109/IBICA.2011.91] [Scopus]
  • Hung, M., Chu, S., Roddick, J.F., Pan, J. and Shieh, C. (2010). An Effective Image Enhancement Method for Electronic Portal Images. In 2nd International Conference on Computational Collective Intelligence - Semantic Web, Social Networks & Multiagent Systems - ICCCI 2010. Berlin: Springer. 2nd International Conference on Computational Collective Intelligence - Semantic Web, Social Networks & Multiagent Systems - ICCCI 2010. Kaohsiung, Taiwan. Nov 2010, pp. 174-183.
    [10.1007/978-3-642-16696-9_19]
  • Shih, H., Chu, S., Roddick, J.F., Hung, M. and Pan, J. (2010). Power Reduction of Wireless Sensor Networks Using Ant Colony Optimization. In 2010 International Conference on Computational Aspects of Social Networks (CASoN 2010) Taiyuan, China: IEEE. 2010 International Conference on Computational Aspects of Social Networks (CASoN 2010) Taiyuan, China. Sep 2010, pp. 464-467.
    [10.1109/CASoN.2010.110]
  • Tang, L., Chu, S. and Roddick, J.F. (2010). Orientation Tree Structure Based Wavelet/VQ Multiple Description Coding. In Proceedings: 2010 First International Conference on Pervasive Computing, Signal Processing and Applications (PCSPA2010) Harbin Institute of Technology, China: IEEE Computer Society. First International Conference on Pervasive Computing, Signal Processing and Applications (PCSPA2010) Harbin, China. Sep 2010, pp. 700-702.
  • Liang, P., Roddick, J.F., Ceglar, A.J., Shillabeer, A. and de Vries, D.B. (2009). Discovering Itemset Interactions. In Bernard Mans, ed. Australian Computer Science Communications. Wellington, NZ: Conferences in Research and Practice in Information Technology (CRPIT). Thirty-Second Australasian Computer Science Conference (ACSC 2009) Wellington, NZ. Jan 2009, pp. 121-128.
    [Web Link]
  • Allwright, A. and Roddick, J.F. (2008). Exploratory Mining over Organisational Communications Data. In John F Roddick, Jiuyong Li, Peter Christen and Paul Kennedy, ed. Data Mining and Analytics 2008: Proceedings of the Seventh Australasian Data Mining Conference (AusDM 2008) Adelaide, SA: Conferences in Research and Practice in Information Technology (CRPIT). Seventh Australasian Data Mining Conference (AusDM'08) Glenelg, SA. Nov 2008, pp. 41-50.
    [Web Link]
  • Ceglar, A.J., Roddick, J.F. and Powers, D.M. (2007). CURIO: A fast outlier and outlier cluster detection algorithm for large datasets. In Kok-Leong Ong, Wenyuan Li, Junbin Gao, ed. Integrating Artificial Intelligence and Data Mining: Proceedings of the 2nd International Workshop on Integrating Artificial Intelligence and Data Mining (AIDM 2007) Sydney, NSW: Australian Computer Society. Second International Workshop on Integrating AI and Data Mining (AIDM 2007) Gold Coast, Australia. Dec 2007, pp. 37-45.
    [Web Link]
  • Liang, P. and Roddick, J.F. (2007). Detecting Anomalous Longitudinal Associations through Higher Order Mining. In Kok-Leong Ong, Wenyuan Li and Junbin Gao, ed. Integrating Artificial Intelligence and Data Mining: Proceedings of the 2nd International Workshop on Integrating Artificial Intelligence and Data Mining (AIDM 2007) Sydney, NSW: Australian Computer Society. Second International Workshop on Integrating AI and Data Mining (AIDM 2007) Gold Coast, Queensland. Dec 2007, pp. 19-27.
    [Web Link]
  • Roddick, J.F. and Fule, P. (2007). SemGrAM - Integrating semantic graphs into association rule mining. In Peter Christen, Paul Kennedy, Jiuyong Li, Inna Kolyshkina and Graham Williams, ed. Data Mining and Analytics 2007: Proceedings of the 6th Australasian Data Mining Conference (AusDM 2007) Sydney, NSW: Australian Computer Society. 6th Australasian Data Mining Conference (AusDM 2007) Gold Coast, QLD. Dec 2007, pp. 129-137.
    [Web Link]
  • Roddick, J.F., Ceglar, A.J. and de Vries, D.B. (2007). Towards active conceptual modelling for sudden events. In John Grundy, Sven Hartmann, Alberto H.F. Laender, Leszek Maciaszek and John F. Roddick, ed. Challenges in Conceptual Modelling: Tutorials, posters, panels and industrial contributions at the 26th International Conference on Conceptual Modeling: ER 2007. Sydney, NSW: Australian Computer Society. 26th International Conference on Conceptual Modeling. Auckland, New Zealand. Nov 2007, pp. 203-208.
    [Web Link]
  • Shillabeer, A. and Roddick, J.F. (2007). Establishing a lineage for medical knowledge discovery. In Peter Christen, Paul Kennedy, Jiuyong Li, Inna Kolyshkina and Graham Williams, ed. Data Mining and Analytics 2007: Proceedings of the 6th Australasian Data Mining Conference (AusDM 2007) Sydney, NSW: Australian Computer Society. 6th Australasian Data Mining Conference (AusDM 2007) Gold Coast, QLD. Dec 2007, pp. 29-37.
    [Web Link]
  • Chan, D. and Roddick, J.F. (2006). Local nulls in summarised mobile and distributed databases. In A Zanski, S.A. Temis, C.A. Brebbia, N.F.F.Ebecken, ed. Data mining VII: data text and web mining and their business applications. Southampton, UK: WIT Press. Seventh International Conference on Data, Text and Web Mining and their Business Applications and Management Information Engineering. Prague, Czech Republic. Jul 2006, pp. 407-416.
    [10.2495/DATA060411] [Scopus]
  • Ceglar, A.J., Morrall, R. and Roddick, J.F. (2006). Mining medical administrative data: the PKB system. In Markus Ackermann, Carlos Soares, Bettina Guidemann, ed. Proceedings of the ECML/PKDD 2006 Workshop on Practical Data Mining. Heidelberg: SAS Deutschland, Heidelberg. ECML/PKDD 2006 Workshop on Practical Data Mining: Applications, Experiences and Challenges. Berlin, Germany. Sep 2006.
  • Mooney, C.H. and Roddick, J.F. (2006). Marking time in sequence mining. In Peter Christen et al., ed. Proceedings of the fifth Australasian conference on Data mining and analystics. Sydney, NSW: Australian Computer Society. Fifth Australasian conference on Data mining and analystics. Sydney, NSW. Nov 2006, pp. 129-134.
    [Web Link]
  • Shillabeer, A., Roddick, J.F. and de Vries, D.B. (2006). On the arguments against the application of data mining to medical data analysis. In Niels Peek and Carlo Combi, workshop chairs., ed. IDAMAP 2006: Proceedings of the Intelligent Data Analysis in Biomedicine and Pharmacology Conference. Verona, Italy: IDAMAP. IDAMAP 2006 - Intelligent Data Analysis in Biomedicine and Pharmacology. Verona, Italy. Aug 2006.
  • Roddick, J.F. and de Vries, D.B. (2006). Reduce, reuse, recycle: practical approaches to schema integration, evolution and versioning. In Lecture Notes in Computer Science. Heidelberg, Germany: Springer. 4th International Workshop on Evolution and Change in Data Management. Tucson, USA, pp. 209-216.
    [10.1007/11908883_26] [Scopus]
  • Rice, S., Roddick, J.F. and de Vries, D.B. (2006). Defining and implementing domains with multiple types using mesodata modelling techniques. In Stumptner, M., Hartmann, S. and Kiyoki, Y, ed. Proceedings of the Third Asia-Pacific Conference on Conceptual Modelling (APCCM2006) Sydney, NSW: Australian Computer Society. Conceptual Modelling 2006: The 3rd Asia-Pacific Conference on Conceptual Modelling. Hobart, TAS. Jan 2006, pp. 85-93.
    [Web Link]
  • Winarko, E. and Roddick, J.F. (2005). Discovering richer temporal association rules from interval-based data. In Tjoa, AM; Trujillo, J, ed. Lecture Notes in Computer Science. Berlin, Germany: Springer. 7th International Conference on Data Warehousing and Knowledge Discovery. Copenhagen, Denmark. Aug 2005, pp. 315-325.
    [10.1007/11546849_31] [Scopus]
  • Chu, S., Roddick, J.F., Su, C. and Pan, J. (2004). Constrained ant colony optimization for data clustering. In Chengqi Zhang, Hans W. Guesgen, Wai K. Yeap, ed. Trends in Artificial Intelligence: Proceedings of the 8th Pacific Rim International Conference on Artificial Intelligence. Berlin: Springer. 8th Pacific Rim International Conference on Artificial Intelligence. Auckland, New Zealand, pp. 534-543.
    [Scopus]
  • Fule, P. and Roddick, J.F. (2004). Detecting privacy and ethical sensitivity in data mining results. In Vladimir Estivill-Castro, ed. Proceedings of the 27th Australasian conference on computer science. Sydney, NSW: Australian Computer Society. 27th Australasian conference on computer science (ACSC) Dunedin, NZ, pp. 159-166.
  • de Vries, D.B., Rice, S. and Roddick, J.F. (2004). In support of mesodata in database management systems. In Fernando Galindo, Makoto Takizawa and Roland Traunmuller, ed. Proceedings of the 15th International Conference on Database and Expert systems Applications. Berlin: Springer. 15th International Conference on Database and Expert Systems Applications (DEXA 2004) Zaragoza, Spain.
  • Mooney, C.H. and Roddick, J.F. (2004). Mining relationships between interacting episodes. In Proceedings of the Fourth SIAM International Conference on Data Mining. Orlando, USA: SIAM. Proceedings of the Fourth SIAM International Conference on Data Mining. Orlando, USA.
    [Scopus] [Web Link]
  • Mooney, C.H., de Vries, D.B. and Roddick, J.F. (2004). A multi-level framework for the analysis of sequential data. In Simeon J. Simoff and Graham J. Williams, ed. Proceedings of the 3rd Australasian Data Mining Conference. Sydney, NSW: UTS. 3rd Australasian Data Mining Conference. Cairns, NT, pp. 199-213.
  • de Vries, D.B. and Roddick, J.F. (2004). Facillitating database attribute domain evolution using mesodata. In Lecture Notes in Computer Science. New York, USA: Springer. Third International Workshop on Evolution and Change in Data Management (ECDM2004) pp. 429-440.
    [10.1007/b101694] [Scopus]
  • Chu, S., Roddick, J.F., Lu, Z., Pan, J. and Abebe, D.B. (2004). Hadamard transform based Equal-average Equal-variance Equal-norm nearest neighbor codeword search algorithm. In Proceedings of the IEEE International Conference on Multimedia and Expo (ICME2004) New York, USA: Institute of Electrical and Electronic Engineers. ICME2004. Taipei, Taiwan, pp. 671-674.
    [Scopus]
  • Fule, P. and Roddick, J.F. (2004). Experiences in building a tool for navigating association rule result sets. In James Hogan et al., ed. Proceedings of the Australian Workshop on Data Mining and Web Intelligence: ACSW Frontiers. Adelaide, SA: Australian Computer Society. Australasian Workshop on Data Mining and Web Intelligence. Dunedin, NZ. Jan 2004, pp. 103-108.
    [Web Link]
  • Chan, D. and Roddick, J.F. (2003). Context-sensitive mobile database summarisation. In Oudshoorn, M, ed. Computer Science 2003. Bedford Park, South Australia: Australian Computer Society. 26th Australasian Computer Science Conference (ACSC2003) Adelaide, SA. Jan 2003, pp. 140-149.
  • Ceglar, A.J., Roddick, J.F., Mooney, C.H. and Calder, P.R. (2003). From rule visualisation to guided knowledge discovery. In Simoff, S. JWilliams, G. JHegland, M, ed. ADMO 3 : Proceedings of the Australasian Data Mining Workshop. Sydney, NSW: University of Technology, Sydney. Second Australasian Data Mining Workshop (ADM'03) Canberra, ACT. Dec 2003, pp. 59-94.
  • Chu, S., Roddick, J.F., Lu, Z. and Pan, J. (2003). VQ-based watermarking method using labelled bisecting k-means clustering algorithm. In Feng, PSriskanthan, N, ed. 7th International Symposium on Consumer Electronics - 2003. Singapore: INSTITUTE OF ELECTRICAL AND ELECTRONIC ENGINEERS. The 7th International Symposium on Consumer Electronics. Sydney, NSW. Dec 2003.
  • Winarko, E. and Roddick, J.F. (2003). Relative temporal association rule mining. In Simoff, S. JWilliams, G. LHegland, M, ed. ADMO 3 : Proceedings of the Australasian Data Mining Workshop. Sydney, NSW: University of Technology, Sydney. Second Australasian Data Mining Workshop (ADM'03) Canberra, ACT. Dec 2003, pp. 121-142.
  • Roddick, J.F., Hornsby, K. and de Vries, D.B. (2003). A unifying semantic distance model for determining the similarity of attribute values. In Oudshoorn, M, ed. Computer Science 2003: Proceedings of the Twenty-Sixth Australasian Computer Science Conference. Bedford Park, South Australia: Australian Computer Society. 26th Australasian Computer Science Conference (ACSC2003) Adelaide, SA. Jan 2003, pp. 111-118.
  • Chu, S., Roddick, J.F., Pan, J. and Su, C. (2003). Parallel ant colony systems. In Zhong, NZbigniew, W. RShusaku, TEinoshin, S, ed. Foundations of Intelligient Systems. Japan: Springer-Verlag. The 14th International Symposium on Methodologies for Intelligient Systems. Maebashi City, Japan. Oct 2003.
  • Chu, S., Roddick, J.F. and Pan, J. (2002). An Efficient K-medoids-based Algorithm Using Previous Medoid Index, Triangular Inequality Elimination Criteria and Partial Distance Search. In Data Warehousing and Knowledge Discovery [LNCS] Heidelberg: Springer-Verlag. The 4th International Conference on Data Warehousing and Knowledge Discovery 2002. Aix-en-Provence, France. Sep 2002, pp. 301-311.
    [10.1007/3-540-46145-0_7]
  • Chu, S., Roddick, J.F. and Pan, J. (2002). An incremental multi-centred, multi-run sampling scheme for K-medoids-based algorithms. In Data Mining III. UK: WIT PRESS. The 3rd International Conference on Data Mining and Databases for Engineering, Finance and Other Fields. Bologna, Italy. Sep 2002, pp. 553-562.
    [10.2495/DATA020531]
  • Chu, S., Roddick, J.F. and Pan, J. (2002). Efficient K-medoids Algorithms using Multi-Centroids with Multi-runs Sampling Scheme. In Workshop on Mining Data across Multiple Customer Touchpoints for CRM. Taipei, Taiwan: Pacific-Asia Conference, on Knowldege Discovery and Data Mining. The Sixth Pacific-Asia Conference on Knowledge Discovery and Data Mining. Taipei, Taiwan. May 2002.
  • Chu, S., Roddick, J.F., Chen, T. and Pan, J. (2002). Efficient search approaches for K-medoids-based algorithms. In Proceedings of the IEEE TENCON'02. Beijing, China: Institute of Electrical and Electronic Engineers. 2002 IEEE Region 10 Technical Conference on Computers Communications Control and Power Engineering. China. Oct 2002, pp. 712a-715a.
    [Scopus]
  • Mooney, C.H. and Roddick, J.F. (2002). Mining itemsets - An approach to longitudinal and incremental association rule mining. In Zanasi, A, ed. Data Mining III. Bath, UK: WIT PRESS. Third International Conference on Data Mining Methods and Databases. Bologna, Italy. Sep 2002, pp. 93-102.
    [10.2495/DATA020101] [Scopus]
  • Roddick, J.F. and Nieuwenhuis, A.L. (2002). Application Rates to Undergraduate Programs in Information Technology in Australian Universities. In Computer Science 2002 : proceedings of the twenty-fifth Australasian Computer Science conference. Bedford Park, SA: Australian Computer Society. Conferences in research and practice in information technology. Melbourne, VIC. Jan 2002, pp. 223-231.
  • Chu, S. and Roddick, J.F. (2001). Pattern clustering using incremental splitting for non-uniformly distributed data. In Baba, N.; Jain, L.C.; Howlett, R.J., ed. Pattern Clustering Using Incremental Splitting for Non-Uniformly Distributed Data. The Netherlands: IOS Press. Fifth International Conference on Knowledge-Based Intelligent Information Engineering Systems and Allied Technologies. Osaka, Japan. Sep 2001.
  • Chu, S., Roddick, J.F. and Pan, J. (2001). A Comparative Study and Extension to K-medoids Algorithms. In Li, D, ed. Fifth International Conference on Optimization: Techniques and applications (ICOTA 2001) Hong Kong: Hong Kong Polytechnic University. Fifth International Conference on Optimization: Techniques and Applications 2001. Hong Kong, China. Dec 2001.
  • Li, J., Wang, Y., Chu, S. and Roddick, J.F. (2014). Kernel self-optimization learning for kernel-based feature extraction and recognition. Information Sciences, 257 pp. 70-80.
    [10.1016/j.ins.2013.08.011]
  • Wang, Y., Qiao, J., Li, J., Fu, P., Chu, S. and Roddick, J.F. (2014). Sparse representation-based MRI super-resolution reconstruction. MEASUREMENT, 47 pp. 946-953.
    [10.1016/j.measurement.2013.10.026]
  • Zhang, D., Qiao, J., Li, J., Qiao, L., Chu, S. and Roddick, J. (2014). Optimizing Matrix Mapping with Data Dependent Kernal for Image Classification. Journal of Information Hiding and Multimedia Signal Processing, 5(1) pp. 72-79.
    [Web Link]
  • Wang, H., Tseng, K., Chu, S., Roddick, J.F. and Li, D. (2013). Bit-Reduced Automaton Inspection for Cloud Security. Journal of Computers, 24(3) pp. 11-18.
    [Web Link]
  • Mooney, C. and Roddick, J.F. (2013). Sequential Pattern Mining - Approaches and Algorithms. ACM Computing Surveys, 45(2) pp. 19.
    [10.1145/2431211.2431218]
  • Li, L., Li, S., Zhu, H., Chu, S., Roddick, J.F. and Pan, J. (2013). An Efficient Scheme for Detecting Copy-move Forged Images by Local Binary Patterns. Journal of Information Hiding and Multimedia Signal Processing, 4(1) pp. 45-56.
    [Scopus] [Web Link]
  • Yan, L., Zheng, W., Chu, S. and Roddick, J.F. (2013). Neighborhood Discriminant Nearest Feature Line Analysis and Its Application to Face Recognition. Journal of Internet Technology, 14(1) pp. 127-132.
    [10.6138/JIT.2013.14.1.13] [Web Link]
  • Liu, F. and Roddick, J.F. (2011). GOPT-Resolution. International Journal of Artificial Intelligence and Soft Computing, 2(4) pp. 334-352.
    [10.1504/IJAISC.2011.042714]
  • Vijayalakshmi, R., Nadarajan, R., Roddick, J.F., Thilaga, M. and Nirmala, P. (2011). FP-GraphMiner - A Fast Frequent Pattern Mining Algorithm for Network Graphs. Journal of Graph Algorithms and Applications, 15(6) pp. 753-776.
    [Web Link]
  • Roddick, J.F. (2009). Schema Vacuuming in Temporal Databases. IEEE Transactions on Knowledge and Data Engineering, 21(4) pp. 744-747.
    [10.1109/TKDE.2008.201] [10.1109/TKDE.2008.201] [Scopus]
  • Chu, S., Roddick, J.F. and Pan, J. (2008). Improved search strategies and extensions to k-medoids-based clustering algorithms. International Journal of Business Intelligence and Data Mining, 3(2) pp. 212-231.
    [10.1504/IJBIDM.2008.020520] [10.1504/IJBIDM.2008.020520] [Scopus]
  • La-Ongsri, S., Roddick, J.F. and de Vries, D.B. (2008). Accommodating mesodata into conceptual modelling methodologies. Information and Software Technology, 50(5) pp. 424-435.
    [10.1016/j.infsof.2007.05.001] [10.1016/j.infsof.2007.05.001] [Scopus]
  • Roddick, J.F., Spiliopoulou, M., Lister, D. and Ceglar, A.J. (2008). Higher order mining. Sigkdd Explorations, 10(1) pp. 5-17.
    [Web Link]
  • Winarko, E. and Roddick, J.F. (2008). A signature-based indexing method for efficient content-based retrieval of relative temporal patterns. IEEE Transactions on Knowledge and Data Engineering, 20(6) pp. 4433994-825-4433994-835.
    [10.1109/TKDE.2008.20] [10.1109/TKDE.2008.20] [Scopus]
  • Winarko, E. and Roddick, J.F. (2007). ARMADA - An Algorithm for Discovering Richer Relative Temporal Association Rules from Interval-based Data. Data and Knowledge Engineering, 63(1) pp. 76-90.
    [10.1016/j.datak.2006.10.009] [10.1016/j.datak.2006.10.009] [Scopus]
  • Ceglar, A.J. and Roddick, J.F. (2007). Incremental Association Mining Using a Closed-Set Lattice. Journal of Research and Practice in Information Technology, 39(1) pp. 35-45.
    [Scopus] [Web Link]
  • Ceglar, A.J. and Roddick, J.F. (2007). GAM: A Guidance Enabled Association Mining Environment. International Journal of Business Intelligence and Data Mining, 2(1) pp. 3-28.
    [10.1504/IJBIDM.2007.012944] [10.1504/IJBIDM.2007.012944] [Scopus]
  • de Vries, D.B. and Roddick, J.F. (2007). The Case for Mesodata: An Empirical Investigation of an Evolving Database System. Information and Software Technology, 49(9-10) pp. 1061-1072.
    [10.1016/j.infsof.2006.11.001] [10.1016/j.infsof.2006.11.001] [Scopus]
  • Ceglar, A.J. and Roddick, J.F. (2006). Association Mining. ACM Computing Surveys, 38(2) pp. 1-42.
    [10.1145/1132956/1132958] [10.1145/1132956/1132958] [Scopus]
  • Ceglar, A.J., Roddick, J.F., Calder, P.R. and Rainsford, C. (2005). Visualising hierarchical associations. Knowledge and Information Systems, 8(3) pp. 257-275.
    [10.1007/s10115-003-0139-0] [10.1007/s10115-003-0139-0] [Scopus]
  • Chan, D. and Roddick, J.F. (2005). Summarisation for mobile databases. Journal of Research and Practice in Information Technology, 37(3) pp. 267-284.
    [Scopus]
  • Chang, J., Chu, S., Roddick, J.F. and Pan, J. (2005). A Parallel Particle Swarm Optimization Algorithm with Communication Strategies. Journal of Information Science and Engineering, 21(4) pp. 809-818.
    [Scopus]
  • Roddick, J.F. and Mooney, C.H. (2005). Linear temporal sequences and their interpretation using midpoint relationships. IEEE Transactions on Knowledge and Data Engineering, 17(1) pp. 133-135.
    [10.1109/TKDE.2005.12] [10.1109/TKDE.2005.12] [Scopus]
  • Chu, S., Roddick, J.F. and Pan, J. (2004). Novel multi-centroid, multi-run sampling schemes for K-mediods-based algorithms. International Journal of Knowledge-Based and Intelligent Engineering Systems, 8 pp. 45-56.
  • Chu, S., Roddick, J.F. and Pan, J. (2004). Ant colony system with communication strategies. Information Sciences, 167(1-4) pp. 63-76.
    [10.1016/j.ins.2003.10.013] [10.1016/j.ins.2003.10.013] [Scopus]
  • Chu, S., Roddick, J.F. and Tsongyi, C. (2004). A genetic clustering algorithm for mean-residual vector quantization. Chinese Journal of Electronics, 13(2) pp. 316-320.
    [Scopus]
  • Roddick, J.F., Egenhofer, M.J., Hoel, E., Papadis, D. and Salzberg, (2004). Spatial, temporal and spatio-temporal databases - hot issues and directions for PhD research. Sigmod Record, 33(2) pp. 126-131.
    [Scopus]
  • Chu, S., Roddick, J.F., Lu, Z. and Pan, J. (2004). A digital image watermarking method based on labeled bisecting clustering algorithm. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, E87-A(1) pp. 282-285.
    [Scopus]
  • Chu, S. and Roddick, J.F. (2003). A clustering algorithm using the tabu search approach with simulated annealing for vector quantization. Chinese Journal of Electronics, 12(3) pp. 349-353.
    [Scopus]
  • Gialamas, A., Beilby, J.J., Pratt, N.L., Henning, R., Marley, J.E. and Roddick, J.F. (2003). Investigating tiredness in Australian general practice. Do pathology tests help in diagnosis? Australian Family Physician, 32(8) pp. 663-666.
    [Scopus]
  • Roddick, J.F. and Spiliopoulou, M. (2002). A survey of temporal knowledge discovery paradigms and methods. IEEE Transactions on Knowledge and Data Engineering, 14(4) pp. 750-767.
    [10.1109/TKDE.2002.1019212] [10.1109/TKDE.2002.1019212] [Scopus]
  • Roddick, J.F. and Nieuwenhuis, A.L. (2001). An Analysis of Application Rates to Programs in Information Technology, Science and Engineering. IEEE Transactions on Education, 44(3) pp. 268-275.
  • Roddick, J.F., Grandi, F., Mandreoli, F. and Scalas, M.R. (2001). Beyond Schema Versioning: A Flexible Model for Spatio-Temporal Schema Selection. Geoinformatica, 5(1) pp. 33-50.
  • Zhang, D., Qiao, J., Li, J., Qiao, L., Chu, S. and Roddick, J. (2014). Optimizing Matrix Mapping with Data Dependent Kernal for Image Classification. Journal of Information Hiding and Multimedia Signal Processing, 5(1) pp. 72-79.
    [Web Link]
  • Mooney, C. and Roddick, J.F. (2013). Sequential Pattern Mining - Approaches and Algorithms. ACM Computing Surveys, 45(2) pp. 19.
    [10.1145/2431211.2431218]
  • Vijayalakshmi, R., Nadarajan, R., Roddick, J.F., Thilaga, M. and Nirmala, P. (2011). FP-GraphMiner - A Fast Frequent Pattern Mining Algorithm for Network Graphs. Journal of Graph Algorithms and Applications, 15(6) pp. 753-776.
    [Web Link]
  • Tang, L., Pan, J., Guo, X., Chu, S. and Roddick, J. (2014). A Novel Approach on Behavior of Sleepy Lizards Based on K-Nearest Neighbor Algorithm. In Witold Pedrycz, Shyi-Ming Chen, ed. Social Networks: A Framework of Computational Intelligence. Switzerland: Springer, pp. 287-311.
    [Web Link]
  • Ceglar, A.J., Morrall, R. and Roddick, J.F. (2010). Mining Medical Administrative Data - The PKB Suite. In Carlos Soares and Rayid Ghani, ed. Data Mining for Business Applications, Frontiers in Artificial Intelligence and Applications. Netherlands: IOS Press, pp. 110-119.
  • Wahlstrom, K., Roddick, J.F., Sarre, W., Estivill-Castro, V. and de Vries, D.B. (2009). Legal and technical issues of privacy preservation in data mining. In John Wang, ed. Encyclopedia of Data Warehousing and Mining. 2nd ed. Hershey, PA, USA: Information Science Reference, pp. 1158-1163.
    [Web Link]
  • Roddick, J.F., Ceglar, A.J., de Vries, D.B. and La-Ongsri, S. (2007). Postponing schema definition: Low Instance-to-Entity Ratio (LItER) modelling. In Peter P Chen and Leah Y Wong, ed. Active Conceptual Modeling of Learning. Berlin: Springer, pp. 206-216.
    [10.1007/978-3-540-77503-4_16]
  • Mooney, C.H., de Vries, D.B. and Roddick, J.F. (2006). A multi-level framework for the analysis of sequential data. In Graham J. Williams and Simeon J. Simoff, ed. Data Mining: Theory, Methodology, Techniques and Applications. Heidelberg, Germany: Springer, pp. 229-243.
  • Chu, S., Shieh, C. and Roddick, J.F. (2004). A tutorial on meta-heuristics for optimization. In Jeng-Shyang Pan, Hsiang-Cheh Huang and Lakhmi C. Jain, ed. INTELLIGENT WATERMARKING TECHNIQUES. Singapore: World Scientific Publishing, pp. 97-132.
  • Roddick, J.F. and Lees, B. (2001). Paradigms for Spatial and Spatio-Temporal Data Mining. In Geographic Data Mining and Knowledge Discovery. London, UK: Taylor and Francis, pp. 33-49.

Professional and community engagement

Professor Roddick has had varied and extensive community interests. Between 1995 and 2000 he was the Minister's Nominee on the Northern Adelaide Development Board (NADB) and between 1997 and 2003 he was an Executive Committee Member, Computer Science Association. Between 2001 and 2003 he was the AVCC Representative on the IT Skills Hub, Melbourne and has also served on various SSABSA Examiners' Committees.

From 1999 to 2003 he was Editor-in-Chief of Journal of Research and Practice in Information Technology (the Australian Computer Society academic journal) and from 1999 until 2008 we was the Foundation Series Editor of the Conferences in Research and Practice in Information Technology series (the Australian Computer Society conference series). He has also been programme and general chair for numerous conferences and workshops.

Expertise for media contact

Subject Titles

  • Engineering - Computer Systems

Interests

  • Data Mining and Knowledge Discovery particularly in medicine and health and in defence systems; data mining in time (longitudinally) and space (location)

Contact

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Phone: +61 8 82015611
Email:
Location: Information, Science & Technology (270)
Postal address: GPO Box 2100, Adelaide 5001, South Australia
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