179 publications (plus other papers under review), including 2 books,
4 edited volumes, 15 book chapters, 44 refereed journal articles, 114 refereed conference papers.
(last updated Jan 2009)
2. Smith, K.
A. and Gupta, J. N. D (eds.), Neural Networks in Business: Techniques and
Applications, Idea Group Publishing,
1. Smith, K.
A., Introduction to Neural Networks and Data Mining for Business
Applications, Eruditions Publishing, Emerald,
4. Abraham, A., Smith, K. A., Jain, R., and Jain, L., (eds.), Journal of Computer and Network Applications, Special Issue on Network and Information Security: A Computational Intelligence Approach, Elsevier Science, vol. 30, no. 1, 2007.
3. Ong, K. L., Smith-Miles, K. A., Lee, V. C. S., and Ng W.
K., Proceedings International Workshop on
Integrating AI and Data Mining (AIDM'06), IEEE Computer Society Press,
2006.
2. Smith, K.
A. (ed.), Computers and Operations Research, Special Issue on
Applications of Neural Networks, Elsevier Science, vol. 32, no. 10, 2005.
1. Gupta, J.
N. D and Smith, K. A. (eds.), Computers and Operations Research, Special
Issue on Neural Networks in Business, Elsevier Science, vol. 27, no. 11-12,
2000 (ISSN 0305-0548).
15. Phua, C. Lee, V., Smith-Miles, K., “The Personal Name
Problem and a Data Mining Solution”, in Wang, J. (ed.), Encyclopaedia of
Data Warehousing and Mining - 2nd Edition, to appear 2008.
14. Smith, K.
A., "Neural Networks for Prediction and Classification", in Wang,
J.(ed.), Encyclopaedia of Data Warehousing and Mining, Information
Science Publishing, vol. 2, pp. 865-869, 2006.
13. Ashrafi, M. Z., Taniar, D.,
Smith, K., “An Efficient Compression Technique for Vertical Mining Methods”, in
D.Taniar (ed.), Research
and Trends in Data Mining Technologies and Applications (Advances in Data
Warehousing and Mining), Chapter 6, Idea Group Publishing, Hershey PA,
2007. (ISBN 1-59904-271-1).
12. Ashrafi, M. Z., Taniar, D., Smith-Miles, K. “Towards Distributed
Association Rule Mining Privacy”, in V. Sugumaran
(ed.), Application of Agents and Intelligent Information Technologies
(Advances in Intelligent Information Technologies), Chapter 11, Idea Group
Press, Hershey PA, 2006. (ISBN 1-59904-265-7)
11. Ashrafi, M.Z., Taniar, D., and
Smith, K.A., "Distributed Association Rule Mining", in Wang, J.(ed.),
Encyclopedia of Data Warehousing and Mining,
Information Science Publishing, vol. 1, pp. 403-407, 2006.
10. Siew, E. G., Smith, K. A., Churilov,
L. and Wassertheil, J., "A longitudinal
comparison of supervised and unsupervised learning approaches to iso-resource grouping for acute healthcare in Australia
", in Saman Halgamuge
and Lipo Wang (Eds.), Classification and
Clustering for Knowledge Discovery, Chapter 21, Studies in Computational
Intelligence, Vol. 4, Springer-Verlag, (ISBN:
3-540-26073-0), 2005.
9. Wang, X.,
Abraham, A. and Smith, K. A., "Soft Computing Paradigms for Web Access
Pattern Analysis ", in Saman Halgamuge
and Lipo Wang (Eds.), Classification and
Clustering for Knowledge Discovery, Chapter 15, Studies in Computational
Intelligence, Vol. 4, Springer-Verlag, (ISBN:
3-540-26073-0), 2005.
8. Dale, M.
and Smith, K. A., "A Porter Framework for Understanding the Strategic
Potential of Data Mining for the Australian Banking Industry", H. Nemati and C. Barko (eds.), Organizational
Data Mining: Leveraging Enterprise Data Resources for Optimal Performance,
Idea Group Publishing, Hershey, Pennsylvania, Chapter 3, pp. 25-45, 2004.
7. Yeo, A. C.
and Smith, K. A., "An Integrated Data Mining Approach to Premium Pricing
for Automobile Insurance Industry", A. Shapiro and L. Jain (eds.), Intelligent Techniques In The Insurance
Industry: Theory and Applications, World Scientific Press, Singapore,
Chapter 5, pp. 199-228, (ISBN: 981-238-718-8), 2003.
6. Yeo, A.
C., Smith, K. A., Willis, R. J. and Brooks, M. "A comparison of soft
computing and traditional approaches for risk classification and claim cost
prediction in the automobile insurance industry", L. Reznik
and V. Kreinovich
(eds.), Soft Computing in Measurement and Information Acquisition,
Studies in Fuzziness and Soft Computing, vol. 127, Springer-Verlag, Chapter 18, pp. 249-261, 2003.
5. Bedingfield, S. and Smith, K. A., "Evolutionary rule
generation and its application to credit scoring", L. Reznik
and V. Kreinovich (eds.), Soft Computing in
Measurement and Information Acquisition, Studies in Fuzziness and Soft
Computing, vol. 127, Springer-Verlag, Chapter 19,
pp. 262-276, 2003.
4. Potvin, J.-Y. and Smith, K. A., "Artificial Neural
Networks", in F. Glover and G. Kochenberger
(eds.), Handbook of Metaheuristics, Chapter
15, Kluwer Academic Publishers, Boston, 2003. (ISBN
1-4020-7263-5)
3. Smith, K.
A. and Lokmic, L., "Combining Supervised and
Unsupervised Neural Networks for Improving Cash Flow Forecasting", in
Smith, K. A. and Gupta, J. N.D (eds.), Neural Networks in Business: Techniques
and Applications, Idea Group Publishing, Hershey, Pennsylvania, Chapter 15,
pp. 236-244, 2002.
2. Yeo, A.
C., Smith, K. A., Willis, R. J., and Brooks, M., "Using Neural Networks to
Model Premium Price Sensitivity of Automobile Insurance Customers", in
Smith, K. A. and Gupta, J. N. D (eds.), Neural Networks in Business:
Techniques and Applications, Idea Group Publishing, Hershey, Pennsylvania,
Chapter 3, pp. 41-54, 2002.
1. Smith, K.
A., "Neural Networks for Business: An Introduction", in Smith, K. A.
and Gupta, J. N. D (eds.), Neural Networks in Business: Techniques and
Applications, Idea Group Publishing,
44. Wang, X., Smith, K. A., and Hyndman, R.,
"Rule induction for forecasting method selection: meta-learning the
characteristics of univariate time series", Neurocomputing, in press 2009.
43. Phua, C., Lee, V. C. S., Gayler,
R, Smith-Miles, K., “On the Communal Analysis Suspicion Scoring for Identity
Crime in Streaming Credit Applications”, European Journal of Operational
Research, vol. 195, pp. 595-612, 2009.
42. Geng, X., Zhou, Z.
H., and Smith-Miles, K., “Individual Stable Space: An Approach to Face
Recognition under Uncontrolled Conditions”, IEEE
Transactions on Neural Networks, vol. 19, no. 8, pp. 1354-1368, 2008.
41. Smith-Miles,
K. A., “Cross-disciplinary perspectives on meta-learning for algorithm
selection”, ACM Computing Surveys, vol. 41, no. 1, article 6, 2008.
40. Geng, X., Zhou, Z.-H., and Smith-Miles, K. A., “Automatic
Age Estimation Based on Facial Aging Patterns”, IEEE Transactions on Pattern
Analysis and Machine Intelligence, vol
29, no. 12, pp. 2234-2240, 2007.
39. Wickramasinghe, K., Alahakoon, D.
and Smith-Miles, K., “A Novel Episodic Associative Memory Model for Enhanced
Classification Accuracy”, Pattern Recognition Letters, vol. 28, no. 10,
pp. 1193-1202, 2007.
38. Ali, S. and
Smith, K. A., “On Optimal Degree Selection for Polynomial Kernel with Support
Vector Machines: Theoretical and Empirical Investigations”, International
Journal of Knowledge-Based and Intelligent Engineering Systems, vol. 11,
pp.1-18, 2007.
37. Ashrafi, M.Z., Taniar, D. and Smith, K., “Redundant association rules
reduction techniques”, International
Journal of Business Intelligence and Data Mining, vol. 2, no. 1, pp. 29-63,
2007.
36. Wang, X., Smith,
K. A., Hyndman, R., “Characteristic-based Clustering for Time Series
Data", Data Mining and Knowledge Discovery, vol. 13, no. 3, pp. 335-364, 2006.
35. Ali, S. and
Smith-Miles, K. A., "Automatic kernel selection for support vector
machines", Neurocomputing, vol. 70, pp.
173-186, 2006.
34. Tan, L., Taniar, D., Smith, K. A., “Maximum entropy estimated
distribution classification model”, International Journal of Hybrid
Intelligent Systems, vol. 3, no. 1,
pp. 1-10, 2006.
33. Ali, S. and
Smith, K. A., "On learning algorithm selection for classification", Applied
Soft Computing, vol. 6, no. 2, pp. 119-138,
2006.
32. Tan, L., Taniar, D., Smith, K. A., “A clustering algorithm based on
an estimated distribution model”, International Journal of Business Intelligence
and Data Mining, vol. 1, no. 2, pp. 229-245, 2005.
31. Ali, S. and
Smith, K. A., "Kernel width selection for SVM classification: a meta
learning approach", International Journal of Data Warehousing and
Mining, vol. 1, pp. 78-97, 2005.
30. Kwok, T. and
Smith, K. A., "Optimization via Intermittency with a Self-Organizing
Neural Network", Neural Computation, vol. 17, pp. 2454-2481, 2005.
29. Churilov, L., Siew, E. G., Smith,
K. A., and Wassertheil, J., “Towards data-driven
acute in-patient classification schemes: a hospital management perspective”, Central European Journal of Operations
Research, vol. 13, no. 4, pp. 365-392, 2005.
28. Churilov, L., Bagirov, A.,
Schwartz, D., Smith, K. A., Dally, M., “Data mining with combined use of
optimisation techniques and self-organizing maps for improving risk grouping
rules”, Journal of Management Information Systems, vol. 21, no. 4, pp.
85-100, 2005.
27. Ashrafi, M. Z., Taniar, D. and
Smith K.A., "PPDAM: Privacy-preserving distributed association rule mining
algorithm", International Journal of Intelligent Information
Technologies, vol. 1, no. 1, pp. 49-69, 2005.
26. Ashrafi, M. Z., Taniar, D. and
Smith K.A, “ODAM: An Optimized Distributed Association Rule Mining Algorithm”, IEEE
Distributed Systems Online, IEEE Computer Society, vol. 5, no. 3, pp 1-18, 2004.
25. Wang X.,
Abraham A., and Smith K.A., "Web Traffic Mining Using a Concurrent Neuro-Fuzzy Approach", Journal of Network and
Computer Application, Elsevier Science, Volume 28, Issue 2, pp. 147-165,
2004.
24. Black, J., Benke, G., Smith K.A., and Fritsch, L., "Artificial
Neural Networks and Job-specific Modules to Assess Occupational Exposure",
Annals of Occupational Hygiene, vol. 48, no. 7, pp. 595-600, 2004.
23. Kwok, T. and
Smith, K. A., "A noisy self-organizing neural network with bifurcation
dynamics for combinatorial optimization", IEEE Transactions on Neural
Networks, vol. 15, no. 1, pp. 84-98,
2004.
22. Beh, C., Smith, K. A. and Webley,
P. A., "The VSA process for oxygen enrichment - process description and
dynamic modelling using neural networks", International Journal of
Smart Engineering System Design, vol. 5, no. 1, pp. 1-9, 2003.
21. Smith, K. A.
and Ng, A., "Web page clustering using a self-organizing map of user
navigation patterns ", Decision Support Systems Journal, special
issue on web data mining, vol. 35, no. 2, pp. 245-256, 2003.
20. Yeo, A. C.
and Smith, K. A., "Implementing a data mining solution for an automobile
insurance company: reconciling theoretical benefits with practical considerations",
Annals of Cases in Information Technology, vol. 5, pp. 63-73, 2003.
19. Smith, K.
A., Abramson, D. and Duke, D., “Hopfield Neural Networks for Timetabling:
Formulations, Methods, and Comparative Results”, International Journal of
Computers and Industrial Engineering, vol. 44, no. 2 pp 283 – 305, 2003.
18. Domingues, J. J., Lozano, S., Calle,
M. and Smith, K. A., "A new method for combinatorial optimization: genetic
neighbourhood search", Neural Network World, vol. 6, pp. 533-547,
2002.
17. Guerrero, F.,
Lozano, S., Smith, K., and Kwok, T., "Manufacturing cell formation using a
new self-organising neural network", International Journal of Computers
and Industrial Engineering, vol. 42, no. 2-4, pp. 377-392, 2002.
16. Yeo, A. C.,
Smith, K. A., Willis, R. J. and Brooks, M., "A mathematical programming
approach to optimise insurance premium pricing within a data mining
framework", Journal of the Operational Research Society, vol. 53,
no. 11, pp. 1197-1203, 2002.
15. Smith, K.
A., Potvin, J-Y., and Kwok, T., "Neural network
models for combinatorial optimization: deterministic, stochastic and chaotic
approaches", Control and Cybernetics, vol. 31, no. 2, pp. 183-216,
2002.
14. Yeo, A. C.,
Smith, K. A., Willis, R. J. and Brooks, M., "Clustering technique for risk
classification and prediction of claim cost in the automobile insurance
industry", International Journal of Intelligent Systems in Accounting,
Finance and Management, vol. 10, pp. 39-50, 2001.
13. Kwok, T. and
Smith, K. A., "Experimental Analysis of Chaotic Neural Network Models for
Combinatorial Optimization under a Unifying Framework", Neural Networks,
vol. 13, no. 7, pp. 731-744, 2000.
12. Smith, K. A.
and Gupta, J. N. D., "Neural
Networks in Business: Techniques and Applications for the Operations Researcher",
Computers and Operations Research, vol. 27, no. 11, pp. 1023-1044, 2000.
11. Smith, K.
A., Willis, R. J., and Brooks, M., "An Analysis of Customer Retention and
Insurance Claim Patterns Using Data Mining: A Case Study", Journal of
the Operational Research Society, vol. 51, no. 5, pp. 532-541, 2000.
10. Smith, K.,
Kim, B. and Sargent, G., "Intelligent approaches
to channel assignment in real wireless communication networks", International
Journal of Smart Engineering System Design, vol. 2, pp. 89-107, 1999.
9. Kwok, T.
and Smith, K. A., "A Unified Framework for Chaotic Neural Network
Approaches to Combinatorial Optimisation", IEEE Transactions on Neural
Networks, vol. 10, no. 4, pp. 978-981, 1999.
8. Smith, K.
"Neural Networks for Combinatorial Optimisation: A review of more than a
decade of research", INFORMS Journal on Computing, vol. 11, no. 1,
pp. 15-34, 1999.
7. Wang, L.
and Smith, K., "On Chaotic Simulated Annealing", IEEE Transactions
on Neural Networks, vol. 9, no. 4, pp. 716-718, 1998.
6. Smith, K.,
Palaniswami, M. and Krishnamoorthy,
M., "Neural Techniques for Combinatorial Optimisation with
Applications", IEEE Transactions on Neural Networks, vol. 9, no. 6,
pp. 1301-1318, 1998.
5. Smith, K,
and Palaniswami, M., "Static and Dynamic Channel
Assignment using Neural Networks", IEEE Journal on Selected Areas in
Communications, vol. 15, no. 2, pp. 238-249, 1997.
4. Smith, K.,
Krishnamoorthy, M. and Palaniswami,
M., "Neural versus Traditional Approaches to the Location of Interacting
Hub Facilities", Location Science, vol. 4, no. 3, pp. 155-171,
1996.
3. Smith, K.,
Palaniswami, M. and Krishnamoorthy,
M., “Traditional Heuristic versus Hopfield Neural Network Approaches to a Car
Sequencing Problem”, European Journal of Operational Research, vol. 93,
no. 2, pp. 300-316, 1996.
2. Smith, K.,
Palaniswami, M. and Krishnamoorthy,
M., “A Hybrid Neural Approach to Combinatorial Optimisation”, Computers and
Operations Research, vol. 23, no. 6, pp. 597-610, 1996.
1. Smith, K.,
“An argument for abandoning the Travelling Salesman Problem as a neural network
benchmark”, IEEE Transactions on Neural Networks, vol. 7, no. 6, pp.
1542-1544, 1996.
Submitted
& Under Review
2. Phua, C., Smith-Miles, K. A., Lee, V. C. S. and Gayler, R., “Resilient Identity Crime Detection”, Data Mining and Knowledge Discovery,
submitted 2007, under 2nd revision.
1. Geng, X., Smith-Miles, K, Wang, L., Li, M., and Wu, Q.
“Context-Aware Multi-Biometric Fusion with Application to Human Identification
in Video”, IEEE Transactions on Image Processing, submitted 2007, under
revision.
114. Smith-Miles, K. A., James, R. J.
W., Giffin, J. and Tu, Y.,
“Understanding the Relationship between Scheduling Problem Structure and
Heuristic Performance using Knowledge Discovery”, Learning in Intelligent Optimization, in press 2009.
113. Phua, C., Lee, V. C.
S., Gayler, R. and Smith-Miles, K., “Utility of
Real-time Decision-making in Commercial Data Stream Mining Domains”, 5th International Conference on
Service Systems and Service Management (ICSSSM'08), in press
2008.
112. Smith-Miles, K. A., "Towards insightful
algorithm selection for optimisation using meta-learning concepts", International Joint Conference on Neural
Networks, Workshop on Hybrid Systems,
Ensembles, and Meta-Learning Algorithms, in press 2008.
111. Geng, X., Wang, L., Li,
M., Wu, Q. and Smith-Miles, K., “Adaptive Fusion of Gait and Face for Human Identification
in Video”, Proceedings IEEE 2008 Workshop on Application of Computer
Vision, in press.
110. Siew, E. G., Churilov, L. Smith-Miles, K.A. and Sturmberg,
J. P., “Using supervised and unsupervised techniques to determine groups of
patients with different continuity of care”, PAKDD 2008, pp. 715-722,
2008.
109. Smith-Miles, K. A., “Generalizing meta-learning
for algorithm selection via Rice’s framework”, in Giraud-Carrier, C. and Vilalta, R. (eds.), Proceedings of the Meta-learning
Workshop, International Joint Conference on Neural Networks, pp. 19-23,
2007 (invited paper).
108. Smith-Miles, K.A. “Generalising meta-learning
concepts: from machine learning to meta-heuristics”, in Proceedings of the 7th
Meta-heuristics International Conference (MIC’07),
107. Smith-Miles, K. A., “Meta-Learning: From
Classification to Forecasting, to Optimization, and Beyond”, Proceedings of the 6th IEEE/ACIS
International Conference on Computer and Information Science (ICIS 2007),
IEEE Computer Society, p. 2, 2007 (keynote address).
106. Phua, C. Lee, V.,
Smith-Miles, K. and Gayler, R., “Adaptive Communal
Detection in Search of Adversarial Identity Crime”. 13th ACM SIGKDD International Conference on Knowledge Discovery and
Data Mining (KDD'07), Workshop on Domain Driven Data Mining
(DDDM'07), pp. 1-10, 2007.
105. Phua, C. Smith-Miles, K. Lee,
V. and Gayler, R., “Adaptive Spike Detection
for Resilient Data Stream Mining”, In Christen, P., Kennedy, P.J., Li, J., Kolyshkina, I. and Williams, G.J., (Eds.), Proc. Sixth
Australasian Data Mining Conference, CRPIT, vol. 70. pp. 181-188, 2007.
104. Geng, X., Wang, L., Li,
M., Wu, Q. and Smith-Miles, K., “Distance-driven Fusion of Gait and Face for
Human Identification in Video”, Proceedings of Image and Vision Computing
New Zealand Conference (ICVNZ’07), pp. 19-24, 2007.
103. Bedingfield S. and
Smith-Miles, K., “Two stage partial classification for inconsistent and
imbalanced classes”, R Munasinghe (ed), 2nd International Conference on Information and
Automation 2006 (ICIA 2006), Colombo, Sri Lanka, 14-17 December 2006, IEEE
Sri Lanka Section, Colombo, Sri Lanka, ISBN: 1-4244-0555-6, pp 167-171, 2006.
102. Amarasiri, R, Alahakoon, D, Smith-Miles, K.A, “Clustering Massive High
Dimensional Data with Dynamic Feature Maps”, Proc. ICONIP, Lecture Notes in
Computer Science, vol. 4233, pp. 814-823, 2006.
101. Ali, S., and Smith-Miles, K., “Improved Support
Vector Machine Generalisation Using Normalized Input Space”, Proceedings of
the 19th Australian Joint Conference on Artificial Intelligence 2006,
Lecture Notes in Artificial Intelligence, vol. 4304, pp. 362-371, 2006.
100. Phua, C., Gayler, R., Smith-Miles, K., and Lee, V., “Communal
Detection of Implicit Personal Identity Streams”, Proc. 6th IEEE International
Conference on Data Mining, workshop on Mining Evolving and Streaming Data, IEEE
Computer Society 2006, ISBN 0-7695-2702-7, pp. 620-625, 2006.
99. Chau, R., Yeh, C. H.,
Smith-Miles, K., "Fuzzy-neuro Web-Based
Multilingual Knowledge Management" Proc. ICONIP, Lecture Notes in
Computer Science, vol. 4223, pp. 1229-1238, 2006.
98. Chau, R. Smith-Miles, K., Yeh, C.
H., “Ontology learning from text: a soft computing paradigm”, ICONIP’06, Lecture Notes in Computer Science, vol.
4234, pp. 295-301, 2006.
97. Phua, C., Lee, V., Gayler, R.,
and Smith, K. A., “Temporal Representation in Spike Detection of Sparse
Personal Identity Streams”, Proceedings of the PAKDD 2006 , Lecture Notes in
Computer Science, Springer-Verlag, vol. 3917, pp.
115-126, 2006.
96. Mafruz Zaman Ashrafi,
David Taniar, Kate Smith, Redundant Association Rules
Reduction Techniques, Proceedings AI2005, pp. 254-263, 2005.
95. Phua C, Gayler R, Lee V and Smith
K., “Empirical Scoring of Anomalous Credit Applications with pair-wise
matching”, Proceedings of Credit Scoring and Credit Control IX, 2005.
94. Wickramasinghe, L.K., Alahakoon,
L.D. and Smith, K.A., “Computation of Meta-Learning Classifiers in Distributed
Data Mining using a Novel Cognitive Memory Model”. IEEE/WIC International
Conference on Intelligent Agent Technology IAT-2005, September 19-22,
France, pp. 180 – 186, 2005.
93. Amarasiri, R, Alahakoon, D, Premaratne, M, Smith, K.A., “HDGSOMr:
A High Dimensional Growing Self Organizing Map using Randomness for Efficient
Web and Text Mining”, Proceedings of the 2005 IEEE/WIC/ACM International
Conference on Web Intelligence, France, pp. 215-221, 2005.
92. Amarasiri, R, Alahakoon, D, Premaratne, M, Smith, K.A., “Enhancing Clustering
Performance of Feature Maps Using Randomness”, Workshop on Self Organizing
Maps (WSOM) 05,
91. X. Wang, K.
A. Smith, and R. J. Hyndman, “Characteristic-based Forecasting for Time-series
Data”, Proceeding of the 25th International Symposium on Forecasting,
San Antonio, Texas June 12-15, 2005.
90. X. Wang, K.
A. Smith, and R. J. Hyndman, “Dimension Reduction for Clustering Time Series
Using Global Characteristics”, Proceedings of the International Conference on
Computing Science 2005, Lecture Notes in Computer Science, Springer-Verlag, Berlin, Heidelberg, vol. 3516, pp. 792-795, May
22-25, Atlanta, 2005.
89. Ashrafi, M.Z., Taniar, D., and
Smith, K., "An Efficient Compression Technique for Frequent Itemset Generation in Association Rule Mining", PAKDD
2005, Lecture Notes in Computer Science, Volume 3518, pp. 125-135, Springer-Verlag, 2005.
88. Chau, R., Yeh, C-H., Smith, K.A.,
"A Personalized Multilingual Web Content Miner: PMWebMiner.
", In O. Gervasi, M.L. Gavrilova,
V. Kumar (Eds.), Computational Science and its Application (ICCSA 2005), Lecture
Notes in Computer Science, Vol. 3481, Springer-Verlag,
Berlin, Heidelberg, Germany, 956-965, 2005.
87. Chau, R., Yeh, C-H., Smith, K.A.,
"A Neural Network Model for Hierarchical Multilingual Text
Categorization", In J. Wang, X. Liao, Z, Yi (Eds.), Advances in Neural
Networks (ISNN 2005), Second International Symposium on Neural Networks, Lecture
Notes in Computer Science, Vol. 3497, Springer-Verlag,
Berlin, Heidelberg, Germany, 238-245, 2005.
86. Amarasiri, R, Alahakoon, D and
Smith, K.A., "HDGSOM: A Modified Growing Self-Organizing Map for High
Dimensional Data Clustering", Proceedings of Hybrid Intelligent Systems,
pp. 216-221, 2004.
85. Amarasiri, R, Alahakoon, D &
Smith, K A, "Applications of the Growing Self Organizing Map on High
Dimensional Data", Proceedings of the 6th International Information
Technology Conference, Sri Lanka, vol. 1, no. 1, pp. 169-174, 2004. Won best paper award.
84. Siew, E-G, Churilov, L, Smith, K
A & Sturmberg, J "Using data mining
techniques to identify groups of patients with different consultation
satisfaction in general practice", Proceedings The Sixth International
Conference on Optimization: Techniques and Applications (ICOTA6 2004) ,
Ballarat, vol. 1, no. 1, pp. 1-12, 2004.
83. Bedingfield, S E & Smith, K A "An Optimisation
Methodology for Multi Parameter Heuristics", Proceedings IEEE 4th
International Conference on Intelligent Systems Design and Application,
vol.1, no.1, pp457-460, 2004.
82. Chau, R, Yeh, C-H & Smith, K
A "Personalized Multilingual Web Content Mining", Lecture Notes in
Artificial Intelligence, vol. 3213, pp. 155-163, 2004.
81. Ashrafi, M Z, Taniar, D &
Smith, K A, "A New Approach of Eliminating Redundant Association
Rules'", Lecture Notes in Computer Science , vol. 3180, no. 1, pp.
465-474, 2004.
80. Ashrafi, M Z, Taniar, D &
Smith, K A, "Reducing Communication Cost in a Privacy Preserving
Distributed Association Rule Mining ", Lecture Notes in Computer
Science , vol. 2973, no. 1, pp. 381-392, 2004.
79. Wang, X., Alahakoon, D. and Smith, K. A., "Neural Network Based
Analysis of Temporal Search Topic Changes in Query Logs", Proceedings
of the 2004 International Conference on Intelligent Agents, Web Technologies,
and Internet Commerce, , vol.1, no.1, pp396-407, 2004.
78. Churilov, L., Bagirov, A. M., Schwartz,
D., Smith, K. A. and Dally, M., "Improving risk grouping rules for
prostate cancer patients with optimization", Proceedings of the 37th
Annual Hawaii International Conference on Systems Sciences, vol.1, no.1,
pp1-9, 2004.
77. Ashrafi, M. Z., Taniar, D. and
Smith, K. A., "A cache-based association rule mining algorithm", Proceedings
of 4th International Conference on Intelligent Technologies, pp. 586-596,
2003.
76. Tan, L., Taniar, D. and Smith, K. A., "Adaptive estimation of
distribution algorithm with maximum entropy principle", Proceedings of
4th International Conference on Intelligent Technologies, 2003, pp.
597-606, 2003.
75. Bedingfield, S. E. and Smith, K. A., “Predicting bad credit
risk: an evolutionary approach", IWANN 2003, Lecture Notes in Computer
Science, vol. 2714, pp. 1081-1088, Springer, 2003.
74. Siew, E-G., Smith, K. A., Churilov,
L. and Wassertheil, J. "A Comparison of Patient
Classification Using Data Mining in Acute Health Care", in A. Abraham, K. Franke, and M. Koppen (eds), Intelligent Systems Design and Applications,
Advances in Soft Computing, pp. 599-609, Springer, 2003.
73. Ashrafi, M. Z., Taniar, D. and
Smith, K. A., "Towards privacy preserving distributed association rule
mining", Proceedings of IWDC 2003, Lecture Notes in Computer Science,
2003, to appear.
72. Ali, S. and
Smith, K. A., "Automatic parameter selection for polynomial kernal", Proceedings of the IEEE International
Conference on Information Reuse and Integration, 2003, to appear.
71. Ali, S.,
Smith, K. A., "Matching SVM Kernel’s Suitability to Data Characteristics
Using Tree by Fuzzy C-means Clustering", in A. Abraham, M. Koppen, K. Franke (eds.), Design
and Application of Hybrid Intelligent Systems, pp. 553-562, IOS Press,
Amsterdam, 2003.
70. Schwartz,
D., Smith, K. A., Churilov, L., Dally, M., Weber, R.,
"Improving Risk Grouping Rules for Prostate Cancer Patients Using
Self-Organizing Maps", in A. Abraham, M. Koppen,
K. Franke (eds.), Design and Application of Hybrid
Intelligent Systems, pp. 126-135, IOS Press, Amsterdam, 2003.
69. Kwok, T.,
Smith, K. A. "A Self-Organising Neural Network with Intermittent Switching
for Combinatorial Optimisation", in A. Abraham, M. Koppen,
K. Franke (eds.), Design and Application of Hybrid
Intelligent Systems, pp. 13-21, IOS Press, Amsterdam, 2003.
68. Calle, M., Lozano, S., Smith, K. A. and Villa, G., "An
XML Schema Definition for an Operations Research Modeling
Language", in A. Abraham, M. Koppen, K. Franke (eds.), Design and Application of Hybrid
Intelligent Systems, pp. 311-320, IOS Press, Amsterdam, 2003.
67. Kwok, T. and
Smith, K. A., "Performance-enhancing bifurcations in a self-organising
neural network ", Computational Methods in Neural Modeling,
Lecture Notes in Computer Science, vol. 2686, Springer-Verlag,
Berlin, Part 1, pp. 390-397, 2003.
66. Ashrafi, M. Z., Taniar, D. and
Smith, K.A., "A compress-based association mining algorithm for large
datasets", Computational Science - ICCS 2003, Lecture Notes in Computer
Science, Springer-Verlag, Berlin, vol. 2660, Part
IV, pp. 978-987, 2003.
65. J.A. Parejo, J. Racero, F. Guerrero,
T. Kwok, and K.A. Smith, "FOM: A framework for metaheuristic
optimization", Computational Science - ICCS 2003, Lecture Notes in
Computer Science, Springer-Verlag, Berlin, vol.
2660, Part IV, pp. 886-895, 2003.
64. Calle, M., Lozano, S., Smith, K.A., Kwok, T. and Domínguez, J., "A DTD for an XML-based Mathematical Modeling Language", Computational Science – ICCS
2003, Lecture Notes in Computer Science, Springer-Verlag,
Berlin, vol. 2660, Part IV, pp. 968-977, 2003.
63. Chau, R., Yeh, C. H., and Smith,
K. A., "Developing a personal multilingual Web space", Proceedings
of IASTED International Conference on Applied Informatics, pp. 145-150,
2003.
62. Wang, X., Alahakoon, D. and Smith, K. A., "Improved web
searching through neural network based index generation", Computational
Science - ICCS 2003, Lecture Notes in Computer Science, Springer-Verlag, Berlin, vol. 2659, Part III, pp. 151-158, 2003.
61. Bedingfield, S. and Smith, K. A., "Evolutionary Rule
Classification and its Application to Multi-Class Data", Computational
Science - ICCS 2003, Lecture Notes in Computer Science, Springer-Verlag, Berlin, vol. 2660, Part IV, pp. 868-876, 2003.
60. Tan, L., Taniar, D., and Smith, K. A., "A Taxonomy for
Inter-Model Parallelism in High Performance Data Mining", Proceedings
of the International Conference On Enterprise Information Systems, volume
1, pp. 534-539, Ciudad Real, Spain, 2002.
59. Tan, L., Taniar, D., and Smith, K. A., "Parametric Optimization
in Data Mining incorporated with GA-based Search", Computational
Science, Lecture Notes in Computer Science vol. 2329, Springer-Verlag, pp. 582-591, 2002.
58. Garcia, J.
M., Smith, K. A., Lozano, S., Guerrero, F. "A comparison of GRASP and an
exact method for solving a production and delivery scheduling problem", in
A. Abraham and M. Koppen (eds.), Hybrid
Information Systems, Physica-Verlag, Heidelberg,
pp. 431-448, 2002.
57. Smith, K.
A., Chuan, S. and van der Putten, P., "Determining the validity of clustering
for data fusion", in A. Abraham and M. Koppen
(eds.), Hybrid Information Systems, Physica-Verlag,
Heidelberg, pp. 627-636, 2002.
56. Smith, K.
A., Woo, F., Ciesielski, V. and Ibrahim, R.,
"Matching data mining algorithm suitability to data characteristics using
a self-organising map", in A. Abraham and M. Koppen
(eds.), Hybrid Information Systems, Physica-Verlag,
Heidelberg, pp. 169-180, 2002.
55. Siew, E., Smith, K. A. and Churilov,
L., "A neural clustering approach
to iso-resource grouping for acute healthcare in
54. Kwok, T. and
Smith, K. A., "Chaotic dynamics of the self-organising neural network with
weight normalisation for combinatorial optimisation", Proceedings of
the Third International NAISO Symposium on Engineering of Intelligent Systems
(EIS’2002), Workshop on Chaos and Computation, Spain, paper no. 112. 2002.
53. Ashrafi, M. Z., Taniar, D. and
Smith, K. A., "A data mining architecture for clustering
environment", Applied Parallel Computing, Lecture Notes in
Computer Science, vol. 2346, Springer-Verlag, pp.
89-98, 2002.
52. Kwok, T.,
Smith, K. A., Lozano, S., Taniar, D., "Parallel
Fuzzy c-Means Clustering for Large Data Sets.", Burkhard
Monien and Rainer Feldmann
(eds.) Euro-Par 2002, Parallel Processing, Proceedings of the 8th
International Euro-Par Conference, Paderborn, Germany, Lecture Notes in
Computer Science, vol. 2400, Springer-Verlag, pp.
365-374. ISBN 3-540-44049-6. 2002.
51. Ashrafi, M. Z., Taniar, D. and
Smith, K. A., "A data mining architecture for distributed
environment", Applied Parallel Computing, Lecture Notes in Computer
Science, vol. 2346, Springer-Verlag, pp. 27-38,
2002.
50. Garcia, J.
M., Lozano, S., Guerrero, F., Smith, K. A., and Calle,
M., "Coordinated scheduling of production and delivery from multiple
plants", 12th International Conference on Flexible Automation and
Intelligent Manufacturing,
49. Tan, L., Taniar, D., and Smith, K.A., "A New Parallel Genetic
Algorithm", Proceedings of The Sixth International Symposium on
Parallel Architectures, Algorithms, and Networks (I-SPAN'02), IEEE Computer
Society Press, pp. 321-326, 2002.
48. Garcia, J.
M., Smith, K. A., Lozano, S., Guerrero, F., Calle,
M., "Production and Delivery Scheduling problem with time windows", Proceedings
of the 30th International Conference on Computers and Industrial Engineering,
pp. 263-268, 2002.
47. Chau, R., Yeh, C.H., and Smith,
K.A., "Multilingual text mining for global knowledge discovery using
self-organising maps", Proceedings of the 2002 International Conference
on Information and Knowledge Engineering, pp. 65-71, 2002.
46. Siew, E., Smith, K. A., Churilov,
L., Wassertheil, J. "A comparison of supervised
and unsupervised approaches to iso-resource grouping
for acute healthcare in Australia", Proceedings of the International
Conference on Fuzzy Systems and Knowledge Discovery, vol. 2, pp. 601-605,
2002.
45. Chand, P., Sugianto, L. F., and
Smith, K. A., "An overview of the Australian energy market and ancillary
services", Proceedings of the AUPEC Conference, 2002.
44. Kwok, T. and
Smith, K. A., "Characteristic updating-normalisation dynamics of a
self-organising neural network for enhanced combinatorial optimisation", Proceedings
of the 9th International Conference on Neural Information Processing,
vol. 3, pp. 1146-1152, 2002.
43. Garcia, J.
M., Lozano, S., Smith, K. A., Kwok, T. and Villa, G., "Coordinated
Scheduling of Production and Delivery From Multiple Plants and with Time
Windows Using Genetic Algorithms", Proceedings of the 9th International
Conference on Neural Information Processing (ICONIP’2002),
42. Wang, X.,
Abraham, A. and Smith, K. A., "Web traffic mining using a concurrent neuro-fuzzy approach", Proceedings of the 2nd
International Conference on Hybrid Intelligent Systems, Chile, Soft Computing
Systems: Design, Management and Applications, IOS Press Amsterdam, The
Netherlands, pp. 853-862, 2002.
41. Wang, X.,
and Smith, K. A., "Clustering web user interests using self-organizing
maps", Proceedings of the 2nd International Conference on Hybrid
Intelligent Systems, Chile, Soft Computing Systems: Design, Management and
Applications, IOS Press Amsterdam, The Netherlands, pp. 843-852, 2002.
40. Wang, X.,
Abraham, A. and Smith, K. A., "Soft computing paradigms for web access
pattern analysis", Proceedings of the International Conference on Fuzzy
Systems and Knowledge Discovery, vol. 2, pp. 631-635, 2002.
39. Ashrafi, M. Z., Taniar, D. and
Smith, K. A., "An association mining algorithm for distributed information
sources", Proceedings of the 4th Asia-Pacific Conference on Simulated
Evolution and Learning, 2002.
38. Garcia, J.
M., Lozano, S., Guerrero, F., Calle, M. and Smith, K.
A., "Production and vehicle scheduling for ready-mix operations", Proceedings
of the 29th International Conference on Computers and Industrial Engineering, pp. 70-76, 2001.
37. Guerrero,
F., Lozano, S., Canca, D., Garcia, J. M. and Smith,
K. A., "A new self-organising neural network for solving the travelling
salesman problem", C. Dagli et al. (Eds.), Smart
Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary
Programming, Data Mining, and Complex Systems, ASME Press, vol. 11, pp.
865-870, 2001.
36. Beh, C. C. K., Smith, K. A. and Webley,
P. A., "Dynamic modelling using neural networks. Case study - pilot scale
VSA process for oxygen production", C. Dagli et
al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy Logic,
Evolutionary Programming, Data Mining, and Complex Systems, ASME Press,
vol. 11, pp. 551-556, 2001.
35. Holl, S. J., Flitman, A. M., and
Smith, K. A., "Hierarchical neural networks for reducing systematic
prediction errors", C. Dagli et al. (Eds.), Smart
Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary
Programming, Data Mining, and Complex Systems, ASME Press, vol. 11, pp.
775-780, 2001.
34. Smith, K.
A., Spithill, T., Coppel,
R. and Smooker, P., "Neural network
classification of malaria protein sequences", C. Dagli
et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy
Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME
Press, vol. 11, pp. 783-788, 2001.
33. Smith, K.
A., Woo, F., Ciesielski, V. and Ibrahim, R.,
"Modelling the relationship between problem characteristics and data
mining algorithm performance using neural networks", C. Dagli et al. (Eds.), Smart Engineering System Design:
Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and
Complex Systems, ASME Press, vol. 11,
pp. 357-362, 2001.
32. Yeo, A. C.,
Smith, K. A., Willis, R. J. and Brooks, M., “Modelling the Effect of Premium
Changes on Insurance Customer Retention Rates Using Neural Networks",
Computational Science, Lecture Notes in Computer Science, vol. 2074,
Springer-Verlag, Berlin, pp. 390-399, 2001.
31. Lozano, S.,
Dominguez, J. J., Guerrero, F. and Smith, K. A., “Genetic line search",
Computational Science, Lecture Notes in Computer Science, vol. 2074,
Springer-Verlag, Berlin, pp. 318-326, 2001.
30. Kwok, T. and
Smith, K. A., "Nonlinear system dynamics in the normalisation process of a
self-organising neural network for combinatorial optimisation",
Connectionist Models of Neurons, Learning Processes, and Artificial
Intelligence, Lecture Notes in Computer Science, vol. 2084, Springer-Verlag, Berlin, pp. 733-740, 2001.
29. Smith, K. A.
and Gupta, J. N. D., “Continuous function optimisation via gradient descent on
a neural network approximation function”, Connectionist Models of Neurons,
Learning Processes, and Artificial Intelligence, Lecture Notes in Computer
Science, vol. 2084, Springer-Verlag, Berlin, pp.
741-748, 2001.
28. Canca, D., Guerrero, F., Smith, K. A. and Lozano, S.,
"Facility location in a competitive environment using metaheuristics",
Proceedings of the 5th on-line World Conference on Soft Computing in
Industrial Applications, pp. 258-263, 2000.
27. Kwok, T. and
Smith, K. A., "Improving the Optimisation Properties of a Self-organising
Neural Network with Weight Normalisation", Proceedings of the ICSC
Symposia on Intelligent Systems and Applications, paper 1513-285, 2000.
26. Ng, A. and
Smith, K. A., “Web usage mining by a self-organizing map”, C. Dagli et al. (Eds.), Smart Engineering System Design:
Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and
Complex Systems, ASME Press, vol. 10, pp. 495-500, 2000 - Nominated,
Best Applications Paper at Conference.
25. Kwok, T. and
Smith, K. A., "A self-organisation neural network with attractor nodes for
combinatorial optimisation”, C. Dagli et al. (Eds.), Smart
Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary
Programming, Data Mining, and Complex Systems, ASME Press, vol. 10, pp.
209-216, 2000.
24. Lozano, S.,
Guerrero, F., Canca, D. and Smith, K. A., “Generation
of route timetables using self-organizing feature maps”, C. Dagli
et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy
Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME
Press, vol. 10, pp. 1063-1068, 2000.
23. Bedingfield, S. and Smith, K. A., "A Comparison of
Fitness Functions for Evolutionary Rule Generation", in M. Mohammadian (ed.), Advances in Intelligent Systems:
Theory and Applications, IOS Press, pp. 102-109, 2000.
22. Lokmic, L. and Smith, K. A., "Cash flow forecasting
using supervised and unsupervised neural networks", International Joint
Conference on Neural Networks, vol. 6, pp. 343-347, 2000.
21. Guerrero,
F., Lozano, S., Smith, K. and Eguia, I.,
"Facility Location using Neural Networks", in Y. Suzuki, S. Ovaska, T. Furuhashi, R. Roy, and
Y. Dote (eds.), Soft Computing in Industrial Applications, Springer-Verlag, London, pp.171-179, 2000.
20. Kwok, T. and
Smith, K. A., "A Performance Comparison of Chaotic Simulated Annealing
Models for Solving the N-Queen Problem", in Y. Suzuki, S. Ovaska, T. Furuhashi, R. Roy, and
Y. Dote (eds.), Soft Computing in Industrial Applications, Springer-Verlag, London, pp.447-458, 2000.
19. Bedingfield, S. and Smith, K. A., "Evolutionary Rule
Generation in an Information System", in C. Dagli
et al. (Eds.), Smart Engineering System Design: Neural Networks, Fuzzy
Logic, Evolutionary Programming, Data Mining, and Complex Systems, ASME
Press, vol. 9, pp. 485-492, 1999 - Nominated, Best Applications Paper at
Conference.
18. Smith, K.
A., Siew, E. G., Milne, B. and Luxford,
K., "Neural networks for software metrics estimation", in C. Dagli et al. (Eds.), Smart Engineering System Design:
Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and
Complex Systems, ASME Press, vol. 9, pp. 1073-1078, 1999.
17. Smith, K.
A., Abramson, D. and Duke, D., "Efficient Timetabling Formulations for Hopfield
Neural Networks", in C. Dagli et al. (Eds.),
Smart Engineering System Design: Neural Networks, Fuzzy Logic, Evolutionary
Programming, Data Mining, and Complex Systems, ASME Press, vol. 9, pp.
1027-1032, 1999.
16. Guerrero,
F., Lozano, S., Smith, K. and Kwok, T., "Manufacturing cell formation
using a new self-organizing neural network", International Conference
on Computers and Industrial Engineering, vol. 1, pp. 668-672, 1999.
15. Smith, K.
A., "A data-driven rule-based neural network model for classification",
Proceedings 6th International Conference on Neural Information
Processing, IEEE Press, vol. 3, pp. 855-860, 1999.
14. Kwok, T. and
Smith, K., "Optimisation by chaotic simulated annealing: a comparative
study", Proceedings International Workshop on Soft Computing in
Industry, pp. 275-280, 1999.
13. Guerrero,
F., Smith, K. and Lozano, S., "Self-organising neural approach for solving
the quadratic assignment problem", Proceedings International Workshop
on Soft Computing in Industry, pp. 13-18, 1999.
12. Lozano, S.,
Guerrero, F., Eguia, I. and Smith, K., "Cell
Formation using Two Neural Networks in Series", in C. Dagli
et al. (Eds.), Intelligent Engineering Systems Through Artificial Neural
Networks: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining,
and Rough Sets, ASME Press, vol. 8, pp. 341-346, 1998.
11. Smith, K.
and Gupta, J., "Integrating Feedforward and
Feedback Neural Networks for Optimisation", in C. Dagli
et al. (Eds.), Intelligent Engineering Systems Through Artificial Neural
Networks: Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining,
and Rough Sets, ASME Press, vol. 8, pp. 69-74, 1998. - Nominated, Best
Theoretical Paper Award at Conference.
10. Kwok, T.,
Smith, K. and Wang, L., "Solving combinatorial optimization problems by
chaotic neural networks", in C. Dagli et al.
(Eds.), Intelligent Engineering Systems Through Artificial Neural Networks:
Neural Networks, Fuzzy Logic, Evolutionary Programming, Data Mining, and Rough
Sets, ASME Press, vol. 8, pp. 317-322, 1998.
9. Abramson,
D., Smith, K., Logethetis, P. and Duke, D.,
"FPGA Based Implementation of a Hopfield Neural Network for Solving
Constraint Satisfaction Problems", Proceedings EuroMicro
Workshop on Computational Intelligence, pp. 688-693, 1998.
8. Guerrero,
F., Lozano, S., Canca, D. and Smith, K.,
"Machine Grouping in Cellular Manufacturing: A Self-Organizing Neural
Network", in A. B. Bulsari et al (eds.)
Engineering Benefits from Neural Networks: Proceedings of the 4th
International Conference on Engineering Applications of Neural Networks,
Systems Engineering Association, Turku, Finland, pp. 374-377, 1998.
7. Smith, K.,
Kim, B. and Sargent, G., "Minimising Channel
Interference in Real Cellular Radio Networks", IEEE Global
Communications Conference, vol. 4, pp. 2192-2197, 1998.
6. Smith, K.,
“A genetic algorithm for the Channel Assignment Problem”, IEEE Global
Communications Conference, vol. 4, pp. 2013-2017, 1998.
5. Kwok, T.,
Smith, K. and Wang, L., “Incorporating Chaos into Hopfield Neural Networks for
Combinatorial Optimisation”, in N. Callaos, O. Omolayole and L. Wang (eds.), Proceedings World Multiconference on Systemics,
Cybernetics and Informatics, vol.1, pp.659-665, 1998.
4. Wang, L.
and Smith, K., “Chaos in the Discretized Analog Hopfield Neural Network and Potential Applications
to Optimization”, IEEE International Conference on Neural Networks, pp.
1679-1684, 1998.
3. Smith, K.
"Optimal Airport Hub Location Using Neural Networks", in C. Dagli et al. (eds.), Intelligent Engineering Systems
Through Artificial Neural Networks: Neural Networks, Fuzzy Logic, Data Mining
and Evolutionary Programming, volume 7, ASME Press, pp. 911-916, 1997.
2. Smith, K.
and Palaniswami, M., "An Improved Hopfield
Network Approach to Channel Assignment in a Cellular Mobile Communications
Network", in C. Dagli et al. (eds.), Intelligent
Engineering Systems Through Artificial Neural Networks: Neural Networks, Fuzzy
Logic and Evolutionary Programming, volume 6, ASME Press, pp. 977-982,
1996.
1. Smith, K.,
"Solving the Generalised Quadratic Assignment Problem using a
Self-Organising Process", Proceedings of the IEEE International
Conference on Neural Networks (ICNN), vol. 4, pp. 1876-1879, 1995. Best
Paper Award at Conference
Submitted and Under Review