Professor Alistair Moffat
- Data structures and algorithms for compression
- Data structures and algorithms for string search
- Information retrieval and web search
Alistair Moffat completed a BSc(Honors) and PhD in 1979 and 1986 respectively, both at the University of Canterbury in New Zealand. Since then he has been a member of the academic staff at the University of Melbourne, where he holds an appointment as Professor of Computer Science (2002). Alistair was Head of the University's Department of Computer Science and Software Engineering for a five-year term from 2007 to 2011, and Associate Dean (Curriculum) in the Melbourne School of Engineering during the period 2007-2009.
Alistair has extensive research interests in the areas of text and index compression, source coding methods, and information retrieval. He is an author of three books (Managing Gigabytes, 1994 and 1999; Compression and Coding Algorithms, 2002; and Programming, Problem Solving and Abstraction with C, 2003); and of more than 150 refereed technical papers. Alistair has also served roles as Chair and Program Chair of a range of conferences, and as an Associate Editor of research journals, including Journal of Information Retrieval, and ACM Transactions on Information Systems.
Alistair was awarded an Australian Carrick Citation for Excellence in Teaching and Learning in the first round of these awards in 2006, and has also been recognized within the University for his teaching contributions. In 2010, he received a Teaching Award from the Melbourne School of Engineering for excellence in teaching, and in recognition of his role as principal architect of the School of Engineering's response to the Melbourne Model changes undertaken between 2006 and 2009.
Alistair has served a term on the ARC College of Experts (2003-2005); was a member of the 2012 New Zealand PBRF Panel; and has been a member of a wide range of review and accreditation committees, both internal and external to the University.
- Petri M, Moffat A. Compact inverted index storage using general-purpose compression libraries. SOFTWARE-PRACTICE & EXPERIENCE. John Wiley & Sons. 2018, Vol. 48, Issue 4. DOI: 10.1002/spe.2556
- Moffat A. Computing Maximized Effectiveness Distance for Recall-Based Metrics. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING. IEEE Computer Society. 2018, Vol. 30, Issue 1. DOI: 10.1109/TKDE.2017.2754371
- Liao K, Moffat A, Petri M, Wirth A. A cost model for long-term compressed data retention. WSDM 2017 - Proceedings of the 10th ACM International Conference on Web Search and Data Mining. 2017. DOI: 10.1145/3018661.3018738
- Krishnan U, Moffat A, Zobel J. A taxonomy of query auto completion modes. ACM International Conference Proceeding Series. 2017, Vol. 2017-December. DOI: 10.1145/3166072.3166081
- Moffat A, Petri M. ANS-based index compression. International Conference on Information and Knowledge Management, Proceedings. 2017, Vol. Part F131841. DOI: 10.1145/3132847.3132888
- Lu X, Moffat A, Shane Culpepper J. Can deep effectiveness metrics be evaluated using shallow judgment pools?. SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2017. DOI: 10.1145/3077136.3080793
- Graham Y, Baldwin T, Moffat A, Zobel J. Can machine translation systems be evaluated by the crowd alone. NATURAL LANGUAGE ENGINEERING. Cambridge University Press. 2017, Vol. 23, Issue 1. DOI: 10.1017/S1351324915000339
- Gog S, Moffat A, Petri M. CSA++: Fast pattern search for large alphabets. Proceedings of the Workshop on Algorithm Engineering and Experiments. 2017.
- Hawking D, Moffat A, Trotman A. Efficiency in information retrieval: introduction to special issue. INFORMATION RETRIEVAL JOURNAL. Kluwer Academic Publishers. 2017, Vol. 20, Issue 3. DOI: 10.1007/s10791-017-9309-7
- Kim Y, Callan J, Culpepper JS, Moffat A. Efficient distributed selective search. INFORMATION RETRIEVAL JOURNAL. Kluwer Academic Publishers. 2017, Vol. 20, Issue 3. DOI: 10.1007/s10791-016-9290-6
- Moffat A, Bailey P, Scholer F, Thomas P. Incorporating User Expectations and Behavior into the Measurement of Search Effectiveness. ACM TRANSACTIONS ON INFORMATION SYSTEMS. Association for Computing Machinery Inc.. 2017, Vol. 35, Issue 3. DOI: 10.1145/3052768
- Buchanan G, McKay D, Velloso E, Moffat A, Turpin A, Scholer F. Only forward? toward understanding human visual behaviour when examining search results. 29th Australian Computer-Human Interaction Conference (OzCHI 2017). 2017, Vol. Part F134477. DOI: 10.1145/3152771.3156165
- Bailey P, Moffat A, Scholer F, Thomas P. Retrieval consistency in the presence of qery variations. SIGIR 2017 - Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2017. DOI: 10.1145/3077136.3080839
- Thomas P, Scholer F, Bailey P, Moffat A. Tasks, queries, and rankers in pre-retrieval performance prediction. ACM International Conference Proceeding Series. 2017, Vol. 2017-December. DOI: 10.1145/3166072.3166079
- Clarke CLA, Culpepper JS, Moffat A. Assessing efficiency-effectiveness tradeoffs in multi-stage retrieval systems without using relevance judgments. INFORMATION RETRIEVAL JOURNAL. Kluwer Academic Publishers. 2016, Vol. 19, Issue 4. DOI: 10.1007/s10791-016-9279-1
View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile