Publications
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Book Chapters
J. Kay, I. Koprinska, K. Yacef (2010). Educational Data Mining to Support Group Work in Software Development Projects, In Handbook of Educational Data Mining, C. Romero, S. Ventura, M. Pechenizkiy and R.S.J.d. Baker (eds), Chapman & Hall/CRC Data Mining and Knowledge Discovery Series.
I. Koprinska and S. Carrato (2003). Segmentation Techniques for Video Sequences in the Domain of MPEG Compressed Data, In Intelligent Integrated Media Communication Techniques, Kluwer Academic Publishers.
M. Kubat, I. Koprinska, and G. Pfurtscheller (1998). Learning to Classify Biological Signals, In Machine Learning, Data Mining and Knowledge Discovery: Methods and Applications, R. Michalski, I. Bratko and M. Kubat (eds.), pp. 409-428, John Wiley and Sons Ltd. [ps.gz]
Journal Papers
D. Perera, J. Kay, I. Koprinska, K. Yacef, O. Zaiane (2009). Clustering and Sequential Data Mining of Online Collaborative Learning Data, IEEE Transactions on Knowledge and Data Engineering, volume 21, issue 6, pp.:759 - 772. [pdf]
J. Chan, I. Koprinska and J. Poon (2008). Semi-supervised Classification Using Bridging, International Journal of Artificial Intelligence Tools, 17(3), pp.415-431.[pdf]
I. Koprinska, J. Poon, J. Clark, J. Chan (2007). Learning to Classify E-mail, Information Sciences, 177, pp.2167-2187, Elsevier. [pdf]
D. Cummins, K. Yacef, I. Koprinska (2006). A Sequence Based Recommender System for Learning Resources, Australian Journal of Intelligent Information Processing Systems, 9(2), pp.49-56 (also in the Proc. Australasian Document Computing Symposium (ADCS'2006), Brisbane, Australia. [pdf]
I. Koprinska and S. Carrato (2002). Hybrid Rule-Based/Neural Approach for Segmentation of MPEG Compressed Video, Multimedia Tools and Applications, 18, pp. 187-212, Springer. [pdf]
I. Koprinska and S. Carrato (2001). Video Segmentation: A Survey, Signal Processing: Image Communication, 16(5), pp. 477-500, Elsevier Science. [ps.gz]
I. Koprinska, G. Pfurtscheller, and D. Flotzinger (1996). Sleep Classification in Infants by Decision Tree-Based Neural Network, Artificial Intelligence in Medicine, v.8(4), pp. 387-401, Elsevier Science
I. Ivanova (Koprinska) and M. Kubat (1995). Initialization of Neural Networks by Means of Decision Trees, Knowledge Based Systems, (special issue on Knowledge-Based Neural Networks), 8(6), pp. 333- 344, Elsevier Science.
Refereed Conference Papers
L. Pizzato, J. Akehurst, C. Silvestrini, I. Koprinska, K. Yacef and J. Kay (2012). The effect of suspicious profiles on people recommenders, in Proceedings of the International Conference on User Modeling and User Adapted Interaction (UMAP'2012), Montreal, Canada, 16-20 July, in press.
I. Koprinska, M. Rana and V. Agelidis (2011). Yearly and Seasonal Models for Electricity Load Forecasting, in Proceedings of the International Joint Conference on Neural Networks (IJCNN'2011), 31 July - 5 August 2011, San Jose, California, USA, IEEE Press, pp.1474-1481.
J. Akehurst, I. Koprinska, K. Yacef, L. Pizzato, J. Kay and T. Rej (2011). CCR — A Content-Collaborative Reciprocal Recommender for Online Dating, in Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI'2011), Barcelona, Spain, 16-22 July, pp. 2199-2204. [pdf]
I. Koprinska (2011). Mining Assessment and Teaching Evaluation Data of Regular and Advanced Stream Students, in Proceedings of the Educational Data Mining Conference (EDM'2011), Eindhoven, The Netherlands, 6-8 July, pp.359-360. [pdf]
L. Pizzato, T. Rej, K. Yacef, I. Koprinska and J. Kay (2011). Finding Someone You Will Like and Who Won't Reject You, in Proceedings of the International Conference on User Modeling and User Adapted Interaction (UMAP'2011), Girona, Span, 11-15 July, pp. 269-280. [pdf]
J. Akehurst, I. Koprinska, K. Yacef, L. Pizzato, J. Kay and T. Rej (2011). Explicit and Implicit User Preferences in Online Dating, in Proceedings of the Behavior Informatics Workshop, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'2011), Shenszen, China, Springer, LNCS, in press.
L. Pizzato, T. Chung, T. Rej, I. Koprinska, K. Yacef and J. Kay (2010). Learning User Preferences in Online Dating, in Proceedings of the Preference Learning Workshop, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010), Barcelona, Spain, 20-24 September. [pdf]
L. Pizzato, T. Rej, T. Chung, I. Koprinska, K. Yacef and J. Kay (2010). Reciprocal Recommender System for Online Dating (demonstration session), in Proceedings of the ACM Conference on Recomemnder Systems (RecSys), Barcelona, Spain, September 26-30, pp.353-354.[pdf]
L. Pizzato, T. Rej, T. Chung, I. Koprinska and J. Kay (2010). RECON - A Reciprocal Recommender for Online Dating, in Proceedings of the ACM Conference on Recomemnder Systems (RecSys), Barcelona, Spain, September 26-30, pp.207-214. [pdf]
L. Pizzato, T. Rej, T. Chung, K. Yacef, I. Koprinska and J. Kay (2010). Reciprocal Recommenders, in Proceedings of the 8th Workshop on Intelligent Techniques for Web Personalization and Recommender Systems, held in conjunction with the 18th International Conference on User Modeling, Adaptation and Personalization (UMAP'2010), 20-24 June 2010, Hawaii, USA. [pdf]
I. Koprinska, R. Sood and V. Agelidis (2010). Variable Selection for Five-Minute Ahead Electricity Load Forecasting, in Proc. 20th International Conference on Pattern Recognition (ICPR'10), 23-26 August 2010, Istanbul, Turkey, pp.2901-2904.
R. Sood, I. Koprinska, V. Agelidis (2010). Electricity Load Foreasting Based on Autocorrelation Analysis, in Proceedings of the International Joint Conference on Neural Networks (IJCNN'10), 18-23 July 2010, Barcelona, Spain, IEEE Press. [pdf]
T. O'Keefe and I. Koprinska (2009). Feature Selection and Weighting in Sentiment Analysis, in Proceedings of the Australasian Document Computing Symposium (ADCS'2009), Sydney, Australia, pp.67-74. [pdf] best student paper award
A. Setiawan, I. Koprinska and V. Agelidis (2009). Very Short-Term Electricity Load Demand Forecasting Using Support Vector Regression, in Proceedings of the International Joint Conference on Neural Networks (IJCNN'2009), 14-19 June 2009, Atlanta, USA, IEEE Press, pp.2888-2894.
I. Koprinska (2009). Comparison of Feature Selection Methods for Classification of Brain-Computer Interface Data, in Proceedings of the Workshop on Advances and Issues in Biomedical Data Mining, Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'2009), 27-30 April, Bangkok, Thailand. An extended version selected for publication in New Frontiers in Applied Data Mining, PAKDD Workshops 2009, Lecture Notes in Artificial Intelligence 5669, Springer, 2010. [pdf]
O. AlZoubi, I. Koprinska and R. Calvo (2008). Classification of Brain-Computer Interface Data, in Proceedings of the Australasian Data Mining Conference (AusDM'2008), 27-28 November, Adelaide, Australia, pp.123-132. [pdf]
J. Chan, J. Poon, I. Koprinska (2007). Enhancing the Performance of Semi-supervised Classification Algorithms with Bridging, in Proceedings of the 20th International Florida Artificial Intelligence Research Society Conference (FLAIRS), AAAI Press, pp.580-586. [on-line proceedings]
Perera, D., J. Kay, K. Yacef and I. Koprinska (2007). Mining Learners' Traces From an Online Collaboration Tool, in Proceedings of the Educational Data Mining Workshop, held in conjunction with AIED'07. Los Angeles, USA, pp.60-69. [on-line proceedings]
I. Koprinska, D. Deng and F. Feger (2006). Image Classification Using Labelled and Unlabelled Data, in Proceedings of the 14th European Signal and Image Processing Conference (EUSIPCO), Florence, Italy, September 2006. [pdf]
F. Feger and I. Koprinska (2006). Co-training Using RBF Nets and Different Feature Splits, in Proceedings of the International Joint Conference on Neural Networks (IJCNN), IEEE Press, Vancouver, Canada, July 2006, pp.1878-1885. [pdf]
D. Ler, I. Koprinska, and S. Chawla (2005). Utilising Regression-Based Landmarkers within a Meta-Learning Framework for Algorithm Selection, In Proceedings of the Workshop on Meta-Learning, 22th International Conference on Machine Learning (ICML), 7-11 August Bonn, Germany, pp.44-51. [earlier version as TR]
D. Ler, I. Koprinska and S. Chawla (2005). A Hill-Climbing Landmarker Generation Algorithm Based on Efficiency and Correlativity Ctiteria, in Proceedings of the 18th International Florida Artificial Intelligence Research Society Conference (FLAIRS), AAAI Press, pp.418-423. [pdf] [TR]
M. Saberi, S. Carrato, I. Koprinska and J. Clark (2005). Estimation of the Hierarchical Structure of a Video Sequence Using MPEG-7 Descriptors and GCS, in Proceedings of the 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems (KES), Lecture Notes in Computer Science 3682, pp.8-15, 14-16 September, Melbourne, Australia.
I. Koprinska and J. Clark (2004). Video Summarization and Browsing Using Growing Cell Structures, in Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN), vol. 4, pp. 2601-2606, IEEE Press, Budapest, Hungary.
D. Ler, I. Koprinska and S. Chawla (2004). A Landmarker Selection Algorithm Based on Correlation and Efficiency Criteria, In Proceedings of the 17th Australian Joint Conference on Artificial Intelligence, Lecture Notes in Computer Science 3339, Springer, Cairns, Australia. [TR]
D. Ler, I. Koprinska, and S. Chawla (2004). A New Landmarker Generation Algorithm Based on Correlativity, in Procrrdings of the ACM/IEEE International Conference on Machine Learning and Applications, Louisville, USA, pp.178-185. [pdf]
D. Ler, I. Koprinska and S. Chawla (2004). Comparison Between Neuristics Based on Corerlativity and Efficiency for Landmarker Generation, in Proceedings of the of 4th International Conference on Hybrid Intelligent systems, Japan, IEEE Computer Society Press. [TR]
I. Koprinska, J. Clark and S. Carrato (2004). VideoGCS – A Clustering-Based System for Video Summarization and Browsing, in Proceedings of the 6th COST 276 Workshop “Information and Knowledge Management for Integrated Media Communication”, Thessaloniki, Greece. [pdf]
E.Crawford, I. Koprinska and J. Patrick (2004). Phrases and Feature Selection in E-mail Classification, in Proceedings of the 9th Australasian Document Computing Symposium (ADCS'04), Melbourne, Australia, pp.59-62. [pdf]
J. Chan, I. Koprinska and J. Poon (2004). Co-training on Textual Documents with a Single Natural Feature Set, in Proceedings of the 9th Australasian Document Computing Symposium (ADCS’2004), Australia, pp.47-54.
J. Chan, I. Koprinska and J. Poon (2004). Co-training with a Single Natural Feature Set Applied to Email Classification, in Proceedings of the IEEE International Conference on Web Intelligence (WI'04), pp. 586-589, IEEE press, Beijing, China, [pdf]
I. Koprinska, F. Trieu, J. Poon and J. Clark (2003). E-mail Classification by Decision Forests, in Proceedings of the Australasian Document Computing Symposium (ADCS’2003), pp.41-46. [pdf]
F. Verhein, J. Kay, I. Koprinska and E. McCreath (2003). Classifying Public Announcements for User Communities, In Proceedings of the Australasian Document Computing Symposium (ADCS’2003), pp. 15-24. [pdf]
J. Clark, I. Koprinska and J. Poon (2003). A Neural Network Based Approach to Automated E-mail Classification, in Proceedings of the IEEE/WIC International Conference on Web Intelligence (WI'2003), IEEE press, Halifax, Canada, October 13-17, pp. 702-705.
H. Mak, I. Koprinska and J. Poon (2003). Web-Based Movie Recommender Using Text Categorization, in Proceedings of the IEEE/WIC Intern. Conference on Web Intelligence (WI'2003), IEEE press, Halifax, Canada, October 13-17, pp. 602-605. [pdf]
J. Clark, I. Koprinska and J. Poon (2003). LINGER - A Smart Personal Assistant for E-mail Classification, in Proceedings of the 13th International Conference on Artificial Neural Networks (ICANN'2003), Istanbul, Turkey, June 26-29, pp.274-277
E.Crawford, I. Koprinska and J. Patrick (2002). A Multi-Learner Approach to E-Mail Classification, in Proceedings of the Seventh Australasian Document Computing Symposium (ADCS'2002), Sydney, Australia. [pdf]
A. Ceguerra and I. Koprinska (2002). Integrating Local and Global Features in Automatic Fingerprint Verification Data, in Proceedings of the International Conference on Pattern Recognition (ICPR'2002), 11-15 August, Quebec City, Canada, vol.3, pp.347-350.
A. Ceguerra and I. Koprinska (2002). Automatic Fingerprint Verification Using Neural Networks, in Proceedings of the Intern. Conference on Artificial Neural Networks (ICANN'2002), Lecture Notes in Computer Science 2415, Jose R. Dorronsoro (ed.), pp.1281-1286, 27-30 August, Madrid, Spain. [pdf]
K. Jackson and I. Koprinska (2002). DNA Microarray Clustering Using Growing Self Organizing Networks, in Proceedings of the 9th International Conference on Neural Information Processing (ICONIP'2002), 18-22 November, Singapore, pp.805-808. [pdf]
I. Koprinska and N. Kasabov (2000). Evolving Fuzzy Neural Network for Camera Operations Recognition, in Proceedings of the International Conference on Pattern Recognition (ICPR'2000), Barcelona, Spain, 3-7 Sept., pp.523-526
D. Deng, I. Koprinska and N. Kasabov (1999). RICBIS: New Zealand Repository for Intelligent Connectionist-Based Information Systems, in Proceedings of the ICONIP'1999 Workshop, Dunedin, NZ, 22-24 Nov., pp.182-187.
M. Kubat and I. Koprinska (1998), Initialization of Neural Network Architectures, in Proceedings of the 2nd International Conference on Non-Linear Problems in Aviation and Aerospace, Daytona Beach, Florida, April 29-May 1.
I. Koprinska and S. Carrato (1998). Video Segmentation of MPEG Compressed Data, in Proceedings of the 5th IEEE International Conference on Electronics, Circuits and Systems (ICECS'98), 7-10 September, Lisboa, Portugal, vol.2, pp. 243-246.
I. Koprinska and S. Carrato (1998). Segmentation of Compressed Video by Learning Vector Quantizer, in Proceedings of the International Conference on Engineering Applications of Neural Networks (EANN'98), 10-12 June 1998, Gibraltar, pp. 9-16. [ps.gz]
I. Koprinska and S. Carrato (1998). Detecting and Classifying Video Shot Boundaries in MPEG Compressed Sequences, in Proceedings of the European Signal Processing Conference (EUSIPCO'98), special session on Multimedia Signal Processing, 8-11 September 1998, Island of Rhodes, Greece, pp. 1729-1732.
I. Koprinska and S. Carrato (1997). Camera Operation Detection in MPEG Video Data by Means of Neural Networks, in Proceedings of the COST 254 Workshop on Emerging Technologies for Communication Terminals, pp. 300-304, Toulouse, France.
G. Agre and I. Koprinska (1996), Case-Based Refinement of Knowledge-Based Neural Networks, in Proceedings of the International Conference on Intelligent Systems: A Semiotic Perspective, October 20-23, Gaithersberg, MD, USA, pp.221-226.
I. Ivanova (Koprinska) and M. Kubat (1995). Decision-Tree Based Neural Network, in Proceedings of the 8th European Conference on Machine Learning (ECML'95), Heraclion, Crete, Greece, April 25-27, pp.295-298, Lecture Notes in Artificial Intelligence 912, Springer, N. Lavrac and S. Wrobel (eds.).
I. Ivanova (Koprinska), G. Pfurtscheller and C. Andrew (1995). AI-Based Classification of Single-Trial EEG Data, in Proceedings of the 17th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Montreal, Canada, September 20-23, pp.703-704.
M. Kubat and I. Ivanova (Koprinska) (1995). Initialization of RBF Networks with Decision Trees, in Proceedings of the 5th Belgian-Dutch Conference on Machine Learning (BENELEARN'95), Brussels, Belgium, September, pp.61-70.
I. Ivanova (Koprinska), G. Pfurtscheller, D. Flotzinger and M. Kubat (1995). Tree-Based Neural Network Classification of EEG Data, in Proceedings of the 3rd European Conference on Engineering and Medicine, Florence, Italy, 30 April - 3 May, pp.429, A. Pedotti and P. Rabischong (eds.)
I. Ivanova (Koprinska) (1994). Integrating Decision Trees and Neural Networks, in Proceedings of the 6th International Conference on Artificial Intelligence: Methodology, Systems, Applications (AIMSA'94), Sofia, Bulgaria, September 21-24, pp.311-320, World Scientific Publ., P. Jorrand and V. Sgurev (eds.).
I. Ivanova (Koprinska), M. Kubat and G. Pfurtscheller (1994). The System TBNN for Learning of 'Difficult' Concepts, in Proceedings of the 4th Belgian-Dutch Conference on Machine Learning (BENELEARN'94), Rotterdam, The Netherlands, June, pp.230-241, J.C. Bioch and S.H. Nienhuys-Cheng (eds.)
Technical Reports
D. Howell and I. Koprinska (2010). WiiPaint++: Painting with the Wii Remote, TR 661, School of Information Technologies, University of Sydney.
D. Ler, D. Abraham, E. Crawford and I. Koprinska (2005). Accurate and Efficient Selection of Voting Ensembles, TR 564, School of Information Technologies, University of Sydney.