Publications

Google Scholar
DBLP
IEEE Explore
ACM

Book Chapters


I. Koprinska and K. Yacef (2015). People-to-People Reciprocal Recommenders, In Recommender Systems Handbook, 2nd edition, F. Ricci, L. Rokach and B. Shapira (eds.), Springer, pp. 545-568.

M. Rana, I. Koprinska, A. Khosravi (2015). Feature Selection for Interval Forecasting of Electricity Demand Time Series Data, In Artificial Neural Networks, Springer Series in Bio-/Neuroinformatics, vol. 4, pp. 445-462, Springer.

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. [pdf]

Journal Papers


A. Al-Ani, I. Koprinska and G. Naik (2017).  Dynamically Identifying Relevant EEG Channels by Utilizing Their Classification Behaviour, Expert Systems with Applications, vol. 83, pp. 273-282, Elsevier. [doi] [pdf]

L. Luo, W. Liu, I. Koprinska and F. Chan (2017).  DAAR: A Discrimination-Aware Association Rule Classifier for Decision Support, Transactions on Large-Scale Data and Knowledge-Centered Systems (TLDKS) vol. 32, pp.47-68, Springer. [doi].

M. Rana and I. Koprinska (2016). Neural Network Ensemble Based Approach for 2D-Interval Prediction of Solar Photovoltaic PowerEnergies, 9(10), pp.829-846, MDPI. [pdf]

M. Rana, I. Koprinska and V. G. Agelidis (2016).  Univariate and Multivariate Methods for Very Short-Term Solar Photovoltaic Power ForecastingEnergy Conversion and Management, 121, pp.380-390, Elsevier. [doi] [pdf]

M. Rana and I. Koprinska (2016).  Forecasting Electricity Load with Advanced Wavelet Neural Networks,  Neurocomputing, 182, pp.118-132, Elsevier. [doi] [pdf]

M. Rana, I. Koprinska and V. G. Agelidis (2015).  2D-Interval Forecasts for Solar Power Production,  Solar Energy, 122, pp.191-203, Elsevier. [doi] [pdf]

I. Koprinska, M. Rana and V. G. Agelidis (2015). Correlation and Instance Based Feature Selection for Electricity Load ForecastingKnowledge-Based Systems, 82, pp.29-40, Elsevier.  [doi] [pdf]

L. Pizzato, T. Rej, J. Akehurst, I. Koprinska, K. Yacef and J. Kay (2012). Recommending People to People: The Nature of Reciprocal Recommenders With a Case Study in Online Dating, User Modeling and User-Adapted Interaction, Springer. [doi] [pdf]

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, 21(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, 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


R. Haidar, I. Koprinska, B. Jeffries (2017).  Sleep Apnea Event Detection from Nasal Airflow Using Convolutional Neural Networks, in Proceedings of the International Conference on Neural Information Processing (ICONIP 2017), Guangzhou, China,14-18 November, in press; nominated for the Best Student Paper Award

L. Luo, B. Li, I. Koprinska, S. Berkovsky and F. Chen
(2017).  Tracking the Evolution of Customer Purchase Behavior Segmentation via a Fragmentation-Coagulation Process,
in Proceedings of the International  Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne, Australia,19-25 August. [pdf] [in the news press conference]

Z. Wang, I. Koprinska and M. Rana (2017).  Solar Power Prediction Using Pattern Sequences, in Proceedings of the International Conference on Artificial Neural Networks (ICANN 2016), Alghero, Italy,  11-15 September, Springer, Lecture Notes in Computer Science, in press.

S. Chow, K. Yacef, I. Koprinska and J. Curran
(2017).  Automated Data-Driven Hints for Python Programming Students, 
in Extended Proceedings of the International ACM Conference on User Modelling, Adaptation and Personalization (UMAP 2017), Bratislava, Slovakia, 9-12 July, in press.

Z. Wang, I. Koprinska and M. Rana (2017).  Solar Power Prediction Using Weather Type Pair Patterns, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2017), Anchorage, USA, 14-19 May, in press.

L. Luo, B. Li, S. Berkovsky, I. Koprinska and F. Chan (2017).  Online Engagement for a Healthier You: A case Study of Web-Based Supermarket Health Program,  in Proceedings of the 2017 World Wide Web Conference (WWW 2017), Alt-Web Science Track, Perth, Australia, 3-7 April. [pdf]

Z. Wang and I. Koprinska (2017).  Solar Power Prediction with Data Source Weighted Nearest Neighbors,  in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2017), Anchorage, USA, 14-19 May, in press.

L. Luo, B. Li, I. Koprinska, S. Berkovsky and F. Chan (2016).  Discovering Temporal Purchase Patterns with Different Responses to Promotions, in Proceedings of the 25th ACM International Conference on Information and Knowledge Management (CIKM 2016), Indianopolis, USA, 24-28 October. [pdf]

J. McBroom, B. Jeffries, I. Koprinska and K. Yacef (2016).  Exploring and Following Students' Strategies When Completing Their Weekly Tasks, in Proceedings of the  International Conference on Educational Data Mining (EDM 2016), Raleigh, USA, 29 June-2 July, pp.609-610. [pdf] [online proceedings]

J. McBroom, B. Jeffries, I. Koprinska and K. Yacef (2016).  Mining Behaviors of Students in Autograding Submission System Logs, in Proceedings of the  International
Conference on Educational Data Mining (EDM 2016), Raleigh, USA, 29 June-2 July, pp.159-166. [pdf] [online proceedings]

M. Rana, I. Koprinska, A. Troncoso and V. Agelidis (2016).  Extended Weighted Nearest Neighbor for Electricity Load Forecasting, in Proceedings of the International Conference on Artificial Neural Networks (ICANN 2016), Barcelona, Spain,  6-9 September, Springer, Lecture Notes in Computer Science, vol. 9887, pp.299-307.

M. Rana, I. Koprinska and V. Agelidis (2016).  Solar Power Forecasting Using Weather Type Clustering and Ensembles of Neural Networks, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada,  24-29 July.

Z. Wang, I. Koprinska and M. Rana (2016). Clustering Based Methods for Solar Power Forecasting, in Proceedings of the  International Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada,  24-29 July.

L. Luo, B. Li, S. Berkovsky, I. Koprinska and F. Chen (2016).  Who will be Affected by Supermarket Health Programs? Tracking Customer Behavior Changes via Preference Modeling, in Proceedings of the  Australasian Pacific Asia Knowledge Discovery and Data Mining Conference (PAKDD 2016), Auckland, New Zealand, 19-22 April. [pdf]

A. Al-Ani, I. Koprinska, G. Naik and R. Khushaba (2016).  A Dynamic Channel Selection Algorithm for the Classification of EEG and EMG data, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2016), Vancouvar, Canada,  24-29 July.

V. Gramoli, M. Charleston, B. Jeffries, I. Koprinska, M. McGrane, A. Viglas and K. Yacef  (2016). Mining Autograding Data in Computer Science Education, in Proceedings of the  Eighteenth Australasian Computing Education Conference (ACE 2016), Canberra, Australia, 2-5 February. [pdf]

L. Luo, W. Liu, I. Koprinska and F. Chen (2015). Discovering Causal Structures from Time Series Data via Enhanced Granger Causality, in Proceedings of the  Australasian Joint Conference on Artificial Intelligence (AI 2015), Canberra, Australia, 30 November-4 December, Springer, Lecture Notes in Artificial Intelligence, vol. 9457. [pdf]

L. Luo, W. Liu, I. Koprinska and F. Chen (2015). Discrimination-Aware Association Rule Mining for Unbiased Data Analytics, in Proceedings of the  International Conference on Big Data Analytics and Knowledge Discovery (DaWaK 2015), Valencia, Spain, 1-4 September, Springer, Lecture Notes in Computer Science, vol. 9263, pp. 108-120. [pdf]

J. Gupta, I. Koprinska and J. Patrick (2015). Automated Classification of Clinical Incident Types, in Proceedings of the  Australian Health Informatics Conference (HIC 2015), Brisbane, Australia, 3-5 August.

L. Luo, I. Koprinska and W. Liu (2015). Discrimination-Aware Classifiers for Student Performance, in Proceedings of the International Conference on Educational Data Mining (EDM 2015), Madrid, Spain, 26-29 June, pp. 384-387. [pdf]

I. Koprinska, J. Stretton and K. Yacef (2015). Students at Risk: Detection and Remediation, in Proceedings of the International Conference on Educational Data Mining (EDM 2015), Madrid, Spain, 26-29 June, pp. 512-515. [pdf]

T. Colombo, I. Koprinska and M. Panella (2015). Maximum Length Weighted Nearest Neighbor Approach for Electricity Load Forecasting, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2015), Killarney, Ireland, 12-17 July. [pdf].

M. Rana, I. Koprinska and V. G. Agelidis (2015). Forecasting Solar Power Generated by Grid Connected PV System Using Ensembles of Neural Networks, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2015), Killarney, Ireland, 12-17 July. [pdf]

I. Koprinska, J. Stretton and K. Yacef (2015). Predicting Student Performance From Multiple Data Sources, in Proceedings of the 17th International Conference on Artificial Intelligence in Education (AIED 2015), Madrid, Spain, 22-26 July. [pdf]

M. Rana, I. Koprinska and A. Troncoso (2014). Forecasting Hourly Electricity Load Profile Using Neural Networks, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2014), Beijing, China, 6-11 July. [pdf].

S. Pareti, T. O'Keefe, I. Konstas, J. Curran and I. Koprinska (2013). Automatically Detecting and Attributing Indirect Quotations, in Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), Seattle, USA, 18-21 October, pp. 989-999. [pdf]

M. Xu, S. Berkovsky, S. Ardon, S.Triukose, A. Mahanti and I. Koprinska (2013). Catch-up TV Recommendations: Show Old Favourites and Find New Ones, in Proceedings of the ACM Conference on Recomemnder Systems (RecSys 2013), Hong Kong, 12-16 October, pp. 285-293. [pdf]

T. O'Keefe, J. Curran, P. Ashwell and I. Koprinska (2013). An Annotated Corpus of Quoted Opinions in News Articles, in Proceedings of the Association of Computtaional Linguistics Conference (ACL 2013), Sofia, Bulgaria, 4-9 August, pp. 516-520. [pdf]

M. Rana, I. Koprinska and A. Khosravi (2013). Feature Selection for Neural Network-Based Interval Forecasting of Electricity Demand Data, in Proceedings of the 23th International Conference on Neural Networks (ICANN 2013), Sofia, Bulgaria, 10-13 September, Springer, Lecture Notes in Computer Science, vol. 8131, pp. 389-396.

M. Rana and  I. Koprinska (2013). Wavelet Neural Networks for Electricity Load Forecasting, in Proceedings of the 23th International Conference on Neural Networks (ICANN 2013), Sofia, Bulgaria, 10-13 September, Springer, Lecture Notes in Computer Science, vol. 8131, pp. 571-578.

I. Koprinska, M. Rana, A. Troncoso and F. Martinez-Alvarez (2013). Combining Pattern Sequence Similarity with Neural Networks for Forecasting Electricity Demand Time Series, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2013), Dallas, USA, 4-10 August. [pdf]

M. Rana, I. Koprinska, A. Khosravi and V. G. Agelidis (2013). Prediction Intervals for Electricity Load Forecasting Using Neural Networks, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2013), Dallas, USA, 4-10 August. [pdf]

I. Koprinska, M. Rana and V. G. Agelidis (2012). Electricity Load Forecasting: A Weekday-Based Approach, in Proceedings of the 22nd International Conference on Neural Networks (ICANN 2012), Lausanne, Switzerland, 11-14 September, Springer, Lecture Notes in Computer Science, vol. 7553, pp. 33-41.[pdf]

M. Rana, I. Koprinska and V. G. Agelidis (2012). Feature Selection for Electricity Load Forecasting, in Proceedings of the 19th International Conference on Neural Information Processing (ICONIP 2012), Doha, Qatar, 12-15 November, Springer, Lecture Notes in Computer Science, vol. 7664, pp. 526-534.

A. Kotillova, I. Koprinska and M. Rana (2012). Statistical and Machine Learning Methods for Electricity Demand Prediction, in Proceedings of the 19th International Conference on Neural Information Processing (ICONIP 2012), Doha, Qatar, 12-15 November, Springer, Lecture Notes in Computer Science, vol. 7664, pp. 535-542. [pdf]

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, Springer, Lecture Notes in Computer Science, vol. 7379, pp. 225--236. [pdf]

M. Xu, S. Berkovsky, I. Koprinska, S. Ardon and K. Yacef (2012). Time-Dependent Clustering of TV Viewers, in Proceedings of UMAP TVM2P 2012 Workshop on TV and Multimedia Personalisation at the 20th Conference on User Modeling, Adaptation and Personalization (UMAP 2012), Montreal, Canada, 16-20 July; CEUR-WS, vol. 872 [pdf]
http://ceur-ws.org/Vol-872/

T. O'Keefe, S. Pareti, J. Curran, I. Koprinska and M. Honnibal (2012). A Sequence Labelling Approach to Quote Attribution, in Proceedings of the International Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL 2012), Jeju, Korea, 12-14 July. [pdf]

M. Rana and I. Koprinska (2012). Electricity Load Forecasting Using Non-decimated Wavelet Prediction Methods With Two-Stage Feature Selection, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), 10-15 June 2012, Brisbane, Australia, IEEE Press.

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, M. Rana and V. G. 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. [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, New Frontiers in Applied Data Mining, Lecture Notes in Computer Science, vol. 7104, pp.15–27.  [doi] [pdf]

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 2010), 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 2010), 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. G. Agelidis (2010). Variable Selection for Five-Minute Ahead Electricity Load Forecasting, in Proc. 20th International Conference on Pattern Recognition (ICPR 2010), 23-26 August 2010, Istanbul, Turkey, pp.2901-2904.

R. Sood, I. Koprinska, V. G. Agelidis (2010). Electricity Load Foreasting Based on Autocorrelation Analysis, in Proceedings of the International Joint Conference on Neural Networks (IJCNN 2010), 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. G. 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.  [pdf]

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, Springer, Lecture Notes in Artificial Intelligence, vol. 5669, pp.106-117. [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 2007), AAAI Press, pp.580-586. [pdf] [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 2007. Los Angeles, USA, pp.60-69. [pdf]

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 2006), 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 2006), 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 2005), 7-11 August Bonn, Germany, pp.44-51.[pdf] [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 2005), 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 2005), Springer, Lecture Notes in Computer Science, vol.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 2004), vol. 4, pp. 2601-2606, IEEE Press, Budapest, Hungary. [pdf]

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, vol.3339, Springer, Cairns, Australia. [pdf] [TR]

D. Ler, I. Koprinska, and S. Chawla (2004). A New Landmarker Generation Algorithm Based on Correlativity, in Proceedings 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 the6th 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 2004), 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 2004), 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, vol.2415, 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 September, 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, New Zealand, 22-24 November, 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 1998), 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 1998), 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 1998), 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 1995), 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 1994), 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 1994), 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.