Book Chapters

• Kay, J., Koprinska, I., Yacef-Cullum, K. (2011). Educational Data Mining to Support Group Work in Software Development Projects. In Cristobal Romero, Sebastian Ventura, Mykola Pechenizkiy, Ryan S J d Baker (Eds.), Handbook of Educational Data Mining, (pp. 173-185). USA: CRC Press.
• Koprinska, I. (2010). Feature Selection for Brain-Computer Interfaces. In Theeramunkong, Nattee, Adeodato, Chawla, Christen, Lenca, Poon, Williams (Eds.), New Frontiers in Applied Data Mining: PAKDD 2009 International Workshops - Lecture Notes in Artificial Intelligence - LNAI Volume 5669, (pp. 106-117). Berlin Heidelberg: Springer.
• Koprinska, I., Carrato, S. (2003). Segmentation techniques for video sequences in the domain of MPEG-compressed data. In Tasic, Najim, Ansorge (Eds.), Intelligent Integrated Media Communication Techniques, (pp. 89-116). Netherlands: Springer.

Journals

• Pizzato, L., Rej, T., Akehurst, J., Koprinska, I., Yacef-Cullum, K., Kay, J. (2013). Recommending people to people: the nature of reciprocal recommenders with a case study in online dating. User Modeling and User-Adapted Interaction, in press.
• Pizzato, L., Akehurst, J., Silvestrini, C., Yacef-Cullum, K., Koprinska, I., Kay, J. (2012). The effect of suspicious profiles on people recommenders. Lecture Notes in Computer Science (LNCS), 7379, 225-236.
• Perera, D., Kay, J., Koprinska, I., Yacef-Cullum, K., Zaiane, O. (2009). Clustering and Sequential Pattern Mining of Online Collaborative Learning Data. IEEE Transactions On Knowledge And Data Engineering, 21(6), 759-772.
• Chan, J., Koprinska, I., Poon, J. (2008). Semi-supervised classification using bridging. International Journal on Artificial Intelligence Tools, 17(3), 415-431.
• Koprinska, I., Poon, J., Clark, J., Chan, J. (2006). Learning to classify e-mail. Information Sciences, Online Article, 1-21.
• Koprinska, I., Carrato, S. (2002). Hybrid Rule-Based/Neural Approach for Segmentation of MPEG Compressed Video. Multimedia Tools and Applications, 18(3), 187-212.
• Koprinska, I., Carrato, S. (2002). Temporal Video Segmentation: A Survey. Signal Processing: Image Communication, 16(5), 477-500.

Conferences

• O'Keefe, T., Pareti, S., Curran, J., Koprinska, I., Honnibal, M. (2012). A Sequence Labelling Approach to Quote Attribution. Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (emnlp-conll 2012), Stroudsburg, PA: Association for Computational Linguistics (ACL).
• Rana, M., Koprinska, I. (2012). Electricity Load Forecasting Using Non-decimated Wavelet Prediction Methods With Two-Stage Feature Selection. 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Piscataway: (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I., Rana, M., Agelidis, V. (2012). Electricity Load Forecasting: A Weekday-Based Approach. 22nd ICANN International Conference on Artificial Neural Networks, Berlin, Germany: Springer.
• Akehurst, J., Koprinska, I., Yacef-Cullum, K., Pizzato, L., Kay, J., Rej, T. (2012). Explicit and Implicit User Preferences in Online Dating. 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011, Heidelberg, Germany: Springer Verlag.
• Rana, M., Koprinska, I., Agelidis, V. (2012). Feature Selection for Electricity Load Prediction. The 19th International Conference on Neural Information Processing (ICONIP2012), Heidelberg: Springer-Verlag.
• Kotillova, A., Koprinska, I., Rana, M. (2012). Statistical and Machine Learning Methods for Electricity Demand Prediction. The 19th International Conference on Neural Information Processing (ICONIP2012), Heidelberg: Springer-Verlag.
• Akehurst, J., Koprinska, I., Yacef-Cullum, K., Pizzato, L., Kay, J., Rej, T. (2011). CCR - A Content-Collaborative Reciprocal Recommender for Online Dating. 22nd International Joint Conference on Artificial Intelligence, Menlo Park, California, USA: AAAI Press.
• Hawson, L., Koprinska, I., McLean, A., McGreevy, P. (2011). Deciphering the cues from riders' legs. 7th International Equitation Science Conference, the Netherlands: Wageningen Academic Publishers.
• Pizzato, L., Rej, T., Yacef-Cullum, K., Koprinska, I., Kay, J. (2011). Finding someone you will like and who won't reject you. 19th International Conference on User Modeling, Adaptation and Personalization, UMAP 2011, Berlin, Heidelberg: Springer.
• Koprinska, I. (2011). Mining Assessment and Teaching Evaluation Data of Regular and Advanced Stream Students. 4th International Conference on Educational Data Mining (EDM 2011), Eindhoven, Netherlands: Technische Universiteit Eindhoven.
• Koprinska, I., Rana, M., Agelidis, V. (2011). Yearly and seasonal models for electricity load forecasting. International Joint Conference on Neutral Networks (IJCNN) 2011, San Jose: (IEEE) Institute of Electrical and Electronics Engineers.
• Sood, R., Koprinska, I., Agelidis, V. (2010). Electricity Load Forecasting Based on Autocorrelation Analysis. 2010 IEEE Congress on Evolutionary Computation (IEEE-CEC) - WCCI 2010, USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Pizzato, L., Rej, T., Chung, T., Koprinska, I., Yacef-Cullum, K., Kay, J. (2010). Reciprocal Recommender System for Online Dating. Fourth ACM Conference on Recommender Systems (RecSys'10), USA: Association for Computing Machinery (ACM).
• Pizzato, L., Rej, T., Chung, T., Yacef-Cullum, K., Koprinska, I., Kay, J. (2010). Reciprocal Recommenders. 8th Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (ITWP 2010), USA: Intelligent Techniques for Web Personalization and Recommender Systems.
• Pizzato, L., Rej, T., Chung, T., Koprinska, I., Kay, J. (2010). RECON: A Reciprocal Recommender for Online Dating. Fourth ACM Conference on Recommender Systems (RecSys'10), USA: Association for Computing Machinery (ACM).
• Koprinska, I., Sood, R., Agelidis, V. (2010). Variable Selection for Five-Minute Ahead Electricity Load Forecasting. 20th International Conference on Pattern Recognition (ICPR 2010), USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I. (2009). Comparison of Feature Selection Methods for Classification of Brain-Computer Interface Data. Workshop on Advances and Issues in Biomedical Data Mining AIBDM 2009 - In association with the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'09), Thailand: Printing House of Thammasat University, Rangsit Campus.
• O'Keefe, T., Koprinska, I. (2009). Feature Selection and Weighting Methods in Sentiment Analysis. 14th Australasian Document Computing Symposium, Sydney, Australia: School of Information Technologies, University of Sydney.
• Setiawan, A., Koprinska, I., Agelidis, V. (2009). Very Short-Term Electricity Load Demand Forecasting Using Support Vector Regression. International Joint Conference on Neural Networks IJCNN 2009, United States: Documentation LLC.
• Al-Zoubi, O., Koprinska, I., Calvo, R. (2008). Classification of Brain-Computer Interface Data. The Seventh Australasian Data Mining Conference (AusDM 2008), Sydney NSW, Australia: Australian Computer Society.
• Chan, J., Poon, J., Koprinska, I. (2007). Enhancing the Performance of Semi-Supervised Classification Algorithms with Bridging. The Twentieth International Florida Artificial Intelligence Research Society Conference, Menlo Park, California: AAAI Press.
• Perera, D., Kay, J., Yacef-Cullum, K., Koprinska, I. (2007). Mining learners' traces from an online collaboration tool. Workshop on Educational Data Mining 2007, online: International Working Group on Educational Data Mining.
• Cummins, D., Yacef-Cullum, K., Koprinska, I. (2006). A Sequence Based Recommender System for Learning Resources. ADCS 2006 11th Australasian Document Computing Symposium, Queensland: Faculty of Information Technology, Queensland University of Technology.
• Feger, F., Koprinska, I. (2006). Co-training Using RBF Nets and Different Feature Splits. 2006 IEEE World Congress on Computational Intelligence - A Joint Conference of the Int Joint Conf on Neural Networks (IJCNN), Fuzzy Systems (FUZZ-IEEE), and Evolutionary Computation (CEC), USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I., Deng, D., Felix, F. (2006). Image Classification Using Labelled And Unlabelled Data. 14th European Signal Processing Conference (EUSIPCO 2006), Europe: EURASIP European Association for Signal, Speech and Image Processing.
• Ler, D., Koprinska, I., Chawla, S. (2005). A Hill-climbing Landmarker Generation Algorithm Based on Efficiency and Correlativity Criteria. The Eighteenth International Florida Artificial Intelligence Research Society Conference - FLAIRS 2005, USA: AAAI Press.
• Ler, D., Koprinska, I., Chawla, S. (2005). Comparisons between Heuristics Based on Correlativity and Efficiency for Landmarker Generation. Fourth International Conference on Hybrid Intelligent Systems - HIS 2004, Los Alamitos, California, USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Saberi, M., Carrato, S., Koprinska, I., Clark, J. (2005). Estimation of the Hierachical Structures of a Video Sequence Using MPEG-7 Descriptors and GCS. 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, Germany: Springer.
• Ler, D., Koprinska, I., Chawla, S. (2005). Utilising Regression-based Landmarkers within a Meta-learning Framework for Algorithm Selection. W10 - Workshop on Meta-Learning : associated with the 22nd International Conference on Machine Learning (ICML 2005), Germany: International Machine Learning Society.
• Ler, D., Koprinska, I., Chawla, S. (2004). A Landmarker Selection Algorithm Based On Correlation And Efficiency Criteria. 17th Australian Joint Conference on Artificial Intelligence, Berlin: Springer.
• Ler, D., Koprinska, I., Chawla, S. (2004). A New Landmarker Generation Algorithm Based On Correlativity. The 2004 International Conference on Machine Learning and Applications (ICMLA'04), USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Chan, J., Koprinska, I., Poon, J. (2004). Co-Training On Textual Documents With A Single Natural Feature Set. The Ninth Australasian Document Computing Symposium (ADCS 2004), Victoria, Australia: Department of Computer Science and Software Engineering, University of Melbourne.
• Chan, J., Koprinska, I., Poon, J. (2004). Co-Training With A Single Natural Feature Set Applied To Email Classification. 2004 IEEE/WIC ACM International Conference on Web Intelligence, Los Alamitos, CA, USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Crawford, E., Koprinska, I., Patrick, J. (2004). Phrases And Feature Selection In E-Mail Classification. The Ninth Australasian Document Computing Symposium (ADCS 2004), Victoria, Australia: Department of Computer Science and Software Engineering, University of Melbourne.
• Koprinska, I., Clark, J. (2004). Video Summarization And Browsing Using Growing Cell Structures. 2004 IEEE International Joint Conference on Neural Networks. (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I., Clark, J., Carrato, S. (2004). Videogcs - A Clustering-Based System For Video Summarizatiion And Browsing. 6th COST 276 Workshop on Information and Knowledge Management for Integrated Media Communication, Greece: Informatics and Telematics Institute, Centre for Research and Technology.
• Clark, J., Koprinska, I., Poon, J. (2003). A neural network based approach to automatee e-mail classification. 2003 IEEE/WIC Intenational Conference on Web Intelligence, United States: (IEEE) Institute of Electrical and Electronics Engineers.
• Verhein, F., Kay, J., Koprinska, I., McCreath, E. (2003). Classifying public announcements for user communities. Eighth Australasian Document Computing Symposium, Canberra: CSIRO ICT Centre.
• Koprinska, I., Trieu, F., Poon, J., Clark, J. (2003). E-mail classification by decision forests. Eighth Australasian Document Computing Symposium, Canberra: CSIRO ICT Centre.
• Mak, H., Koprinska, I., Poon, J. (2003). INTIMATE: A web-based movie recommender using text categorization. 2003 IEEE/WIC Intenational Conference on Web Intelligence, United States: (IEEE) Institute of Electrical and Electronics Engineers.
• Clark, J., Koprinska, I., Poon, J. (2003). Linger - a smart personal assistant for e-mail classification. 2003 IEEE/WIC Intenational Conference on Web Intelligence, United States: (IEEE) Institute of Electrical and Electronics Engineers.
• Crawford, E., Koprinska, I., Patrick, J. (2002). A Multi-Learner Approach to E-mail Classification. ADCS '02 The Seventh Australasian Document Computing Symposium, Sydney, Australia: School of Information Technologies, University of Sydney.
• Ceguerra, A., Koprinska, I. (2002). Automatic Fingerprint Verification Using Neural Networks. Artificial Neural Networks ICANN 2002 International Conference, Germany: Springer.
• Jackson, K., Koprinska, I. (2002). DNA Microarray Data Clustering Using Growing Self Organizing Networks. 9th International Conference on Neural Information Processing (ICONIP''02) 4th Asia Pacific Conference on Simulated Evolution and Learning (SEAL''02) 1st International Conference on Fuzzy Systems and Knowledge Discovery (FSKD''02), Singapore: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
• Ceguerra, A., Koprinska, I. (2002). Integrating Local and Global Features in Automatic Fingerprint Verification. 16th International Conference on Pattern Recognition, Los Alamitos, California: (IEEE) Institute of Electrical and Electronics Engineers.

2013

• Pizzato, L., Rej, T., Akehurst, J., Koprinska, I., Yacef-Cullum, K., Kay, J. (2013). Recommending people to people: the nature of reciprocal recommenders with a case study in online dating. User Modeling and User-Adapted Interaction, in press.

2012

• O'Keefe, T., Pareti, S., Curran, J., Koprinska, I., Honnibal, M. (2012). A Sequence Labelling Approach to Quote Attribution. Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (emnlp-conll 2012), Stroudsburg, PA: Association for Computational Linguistics (ACL).
• Rana, M., Koprinska, I. (2012). Electricity Load Forecasting Using Non-decimated Wavelet Prediction Methods With Two-Stage Feature Selection. 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012, Piscataway: (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I., Rana, M., Agelidis, V. (2012). Electricity Load Forecasting: A Weekday-Based Approach. 22nd ICANN International Conference on Artificial Neural Networks, Berlin, Germany: Springer.
• Akehurst, J., Koprinska, I., Yacef-Cullum, K., Pizzato, L., Kay, J., Rej, T. (2012). Explicit and Implicit User Preferences in Online Dating. 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2011, Heidelberg, Germany: Springer Verlag.
• Rana, M., Koprinska, I., Agelidis, V. (2012). Feature Selection for Electricity Load Prediction. The 19th International Conference on Neural Information Processing (ICONIP2012), Heidelberg: Springer-Verlag.
• Kotillova, A., Koprinska, I., Rana, M. (2012). Statistical and Machine Learning Methods for Electricity Demand Prediction. The 19th International Conference on Neural Information Processing (ICONIP2012), Heidelberg: Springer-Verlag.
• Pizzato, L., Akehurst, J., Silvestrini, C., Yacef-Cullum, K., Koprinska, I., Kay, J. (2012). The effect of suspicious profiles on people recommenders. Lecture Notes in Computer Science (LNCS), 7379, 225-236.

2011

• Akehurst, J., Koprinska, I., Yacef-Cullum, K., Pizzato, L., Kay, J., Rej, T. (2011). CCR - A Content-Collaborative Reciprocal Recommender for Online Dating. 22nd International Joint Conference on Artificial Intelligence, Menlo Park, California, USA: AAAI Press.
• Hawson, L., Koprinska, I., McLean, A., McGreevy, P. (2011). Deciphering the cues from riders' legs. 7th International Equitation Science Conference, the Netherlands: Wageningen Academic Publishers.
• Kay, J., Koprinska, I., Yacef-Cullum, K. (2011). Educational Data Mining to Support Group Work in Software Development Projects. In Cristobal Romero, Sebastian Ventura, Mykola Pechenizkiy, Ryan S J d Baker (Eds.), Handbook of Educational Data Mining, (pp. 173-185). USA: CRC Press.
• Pizzato, L., Rej, T., Yacef-Cullum, K., Koprinska, I., Kay, J. (2011). Finding someone you will like and who won't reject you. 19th International Conference on User Modeling, Adaptation and Personalization, UMAP 2011, Berlin, Heidelberg: Springer.
• Koprinska, I. (2011). Mining Assessment and Teaching Evaluation Data of Regular and Advanced Stream Students. 4th International Conference on Educational Data Mining (EDM 2011), Eindhoven, Netherlands: Technische Universiteit Eindhoven.
• Koprinska, I., Rana, M., Agelidis, V. (2011). Yearly and seasonal models for electricity load forecasting. International Joint Conference on Neutral Networks (IJCNN) 2011, San Jose: (IEEE) Institute of Electrical and Electronics Engineers.

2010

• Sood, R., Koprinska, I., Agelidis, V. (2010). Electricity Load Forecasting Based on Autocorrelation Analysis. 2010 IEEE Congress on Evolutionary Computation (IEEE-CEC) - WCCI 2010, USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I. (2010). Feature Selection for Brain-Computer Interfaces. In Theeramunkong, Nattee, Adeodato, Chawla, Christen, Lenca, Poon, Williams (Eds.), New Frontiers in Applied Data Mining: PAKDD 2009 International Workshops - Lecture Notes in Artificial Intelligence - LNAI Volume 5669, (pp. 106-117). Berlin Heidelberg: Springer.
• Pizzato, L., Rej, T., Chung, T., Koprinska, I., Yacef-Cullum, K., Kay, J. (2010). Reciprocal Recommender System for Online Dating. Fourth ACM Conference on Recommender Systems (RecSys'10), USA: Association for Computing Machinery (ACM).
• Pizzato, L., Rej, T., Chung, T., Yacef-Cullum, K., Koprinska, I., Kay, J. (2010). Reciprocal Recommenders. 8th Workshop on Intelligent Techniques for Web Personalization and Recommender Systems (ITWP 2010), USA: Intelligent Techniques for Web Personalization and Recommender Systems.
• Pizzato, L., Rej, T., Chung, T., Koprinska, I., Kay, J. (2010). RECON: A Reciprocal Recommender for Online Dating. Fourth ACM Conference on Recommender Systems (RecSys'10), USA: Association for Computing Machinery (ACM).
• Koprinska, I., Sood, R., Agelidis, V. (2010). Variable Selection for Five-Minute Ahead Electricity Load Forecasting. 20th International Conference on Pattern Recognition (ICPR 2010), USA: (IEEE) Institute of Electrical and Electronics Engineers.

2009

• Perera, D., Kay, J., Koprinska, I., Yacef-Cullum, K., Zaiane, O. (2009). Clustering and Sequential Pattern Mining of Online Collaborative Learning Data. IEEE Transactions On Knowledge And Data Engineering, 21(6), 759-772.
• Koprinska, I. (2009). Comparison of Feature Selection Methods for Classification of Brain-Computer Interface Data. Workshop on Advances and Issues in Biomedical Data Mining AIBDM 2009 - In association with the 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'09), Thailand: Printing House of Thammasat University, Rangsit Campus.
• O'Keefe, T., Koprinska, I. (2009). Feature Selection and Weighting Methods in Sentiment Analysis. 14th Australasian Document Computing Symposium, Sydney, Australia: School of Information Technologies, University of Sydney.
• Setiawan, A., Koprinska, I., Agelidis, V. (2009). Very Short-Term Electricity Load Demand Forecasting Using Support Vector Regression. International Joint Conference on Neural Networks IJCNN 2009, United States: Documentation LLC.

2008

• Al-Zoubi, O., Koprinska, I., Calvo, R. (2008). Classification of Brain-Computer Interface Data. The Seventh Australasian Data Mining Conference (AusDM 2008), Sydney NSW, Australia: Australian Computer Society.
• Chan, J., Koprinska, I., Poon, J. (2008). Semi-supervised classification using bridging. International Journal on Artificial Intelligence Tools, 17(3), 415-431.

2007

• Chan, J., Poon, J., Koprinska, I. (2007). Enhancing the Performance of Semi-Supervised Classification Algorithms with Bridging. The Twentieth International Florida Artificial Intelligence Research Society Conference, Menlo Park, California: AAAI Press.
• Perera, D., Kay, J., Yacef-Cullum, K., Koprinska, I. (2007). Mining learners' traces from an online collaboration tool. Workshop on Educational Data Mining 2007, online: International Working Group on Educational Data Mining.

2006

• Cummins, D., Yacef-Cullum, K., Koprinska, I. (2006). A Sequence Based Recommender System for Learning Resources. ADCS 2006 11th Australasian Document Computing Symposium, Queensland: Faculty of Information Technology, Queensland University of Technology.
• Feger, F., Koprinska, I. (2006). Co-training Using RBF Nets and Different Feature Splits. 2006 IEEE World Congress on Computational Intelligence - A Joint Conference of the Int Joint Conf on Neural Networks (IJCNN), Fuzzy Systems (FUZZ-IEEE), and Evolutionary Computation (CEC), USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I., Deng, D., Felix, F. (2006). Image Classification Using Labelled And Unlabelled Data. 14th European Signal Processing Conference (EUSIPCO 2006), Europe: EURASIP European Association for Signal, Speech and Image Processing.
• Koprinska, I., Poon, J., Clark, J., Chan, J. (2006). Learning to classify e-mail. Information Sciences, Online Article, 1-21.

2005

• Ler, D., Koprinska, I., Chawla, S. (2005). A Hill-climbing Landmarker Generation Algorithm Based on Efficiency and Correlativity Criteria. The Eighteenth International Florida Artificial Intelligence Research Society Conference - FLAIRS 2005, USA: AAAI Press.
• Ler, D., Koprinska, I., Chawla, S. (2005). Comparisons between Heuristics Based on Correlativity and Efficiency for Landmarker Generation. Fourth International Conference on Hybrid Intelligent Systems - HIS 2004, Los Alamitos, California, USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Saberi, M., Carrato, S., Koprinska, I., Clark, J. (2005). Estimation of the Hierachical Structures of a Video Sequence Using MPEG-7 Descriptors and GCS. 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, Germany: Springer.
• Ler, D., Koprinska, I., Chawla, S. (2005). Utilising Regression-based Landmarkers within a Meta-learning Framework for Algorithm Selection. W10 - Workshop on Meta-Learning : associated with the 22nd International Conference on Machine Learning (ICML 2005), Germany: International Machine Learning Society.

2004

• Ler, D., Koprinska, I., Chawla, S. (2004). A Landmarker Selection Algorithm Based On Correlation And Efficiency Criteria. 17th Australian Joint Conference on Artificial Intelligence, Berlin: Springer.
• Ler, D., Koprinska, I., Chawla, S. (2004). A New Landmarker Generation Algorithm Based On Correlativity. The 2004 International Conference on Machine Learning and Applications (ICMLA'04), USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Chan, J., Koprinska, I., Poon, J. (2004). Co-Training On Textual Documents With A Single Natural Feature Set. The Ninth Australasian Document Computing Symposium (ADCS 2004), Victoria, Australia: Department of Computer Science and Software Engineering, University of Melbourne.
• Chan, J., Koprinska, I., Poon, J. (2004). Co-Training With A Single Natural Feature Set Applied To Email Classification. 2004 IEEE/WIC ACM International Conference on Web Intelligence, Los Alamitos, CA, USA: (IEEE) Institute of Electrical and Electronics Engineers.
• Crawford, E., Koprinska, I., Patrick, J. (2004). Phrases And Feature Selection In E-Mail Classification. The Ninth Australasian Document Computing Symposium (ADCS 2004), Victoria, Australia: Department of Computer Science and Software Engineering, University of Melbourne.
• Koprinska, I., Clark, J. (2004). Video Summarization And Browsing Using Growing Cell Structures. 2004 IEEE International Joint Conference on Neural Networks. (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I., Clark, J., Carrato, S. (2004). Videogcs - A Clustering-Based System For Video Summarizatiion And Browsing. 6th COST 276 Workshop on Information and Knowledge Management for Integrated Media Communication, Greece: Informatics and Telematics Institute, Centre for Research and Technology.

2003

• Clark, J., Koprinska, I., Poon, J. (2003). A neural network based approach to automatee e-mail classification. 2003 IEEE/WIC Intenational Conference on Web Intelligence, United States: (IEEE) Institute of Electrical and Electronics Engineers.
• Verhein, F., Kay, J., Koprinska, I., McCreath, E. (2003). Classifying public announcements for user communities. Eighth Australasian Document Computing Symposium, Canberra: CSIRO ICT Centre.
• Koprinska, I., Trieu, F., Poon, J., Clark, J. (2003). E-mail classification by decision forests. Eighth Australasian Document Computing Symposium, Canberra: CSIRO ICT Centre.
• Mak, H., Koprinska, I., Poon, J. (2003). INTIMATE: A web-based movie recommender using text categorization. 2003 IEEE/WIC Intenational Conference on Web Intelligence, United States: (IEEE) Institute of Electrical and Electronics Engineers.
• Clark, J., Koprinska, I., Poon, J. (2003). Linger - a smart personal assistant for e-mail classification. 2003 IEEE/WIC Intenational Conference on Web Intelligence, United States: (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I., Carrato, S. (2003). Segmentation techniques for video sequences in the domain of MPEG-compressed data. In Tasic, Najim, Ansorge (Eds.), Intelligent Integrated Media Communication Techniques, (pp. 89-116). Netherlands: Springer.

2002

• Crawford, E., Koprinska, I., Patrick, J. (2002). A Multi-Learner Approach to E-mail Classification. ADCS '02 The Seventh Australasian Document Computing Symposium, Sydney, Australia: School of Information Technologies, University of Sydney.
• Ceguerra, A., Koprinska, I. (2002). Automatic Fingerprint Verification Using Neural Networks. Artificial Neural Networks ICANN 2002 International Conference, Germany: Springer.
• Jackson, K., Koprinska, I. (2002). DNA Microarray Data Clustering Using Growing Self Organizing Networks. 9th International Conference on Neural Information Processing (ICONIP''02) 4th Asia Pacific Conference on Simulated Evolution and Learning (SEAL''02) 1st International Conference on Fuzzy Systems and Knowledge Discovery (FSKD''02), Singapore: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
• Koprinska, I., Carrato, S. (2002). Hybrid Rule-Based/Neural Approach for Segmentation of MPEG Compressed Video. Multimedia Tools and Applications, 18(3), 187-212.
• Ceguerra, A., Koprinska, I. (2002). Integrating Local and Global Features in Automatic Fingerprint Verification. 16th International Conference on Pattern Recognition, Los Alamitos, California: (IEEE) Institute of Electrical and Electronics Engineers.
• Koprinska, I., Carrato, S. (2002). Temporal Video Segmentation: A Survey. Signal Processing: Image Communication, 16(5), 477-500.