Professor Alistair Moffat

  • Room: Level: 09 Room: 9.26
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Data structures and algorithms for compression
  • Data structures and algorithms for string search
  • Information retrieval and web search

Personal webpage

http://people.eng.unimelb.edu.au/ammoffat

Biography

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.


Alistair has been teaching programming to undergraduate students at the University for more than 32 (100000 in binary!) years, and has influenced an entire generation of Engineering and Science graduates. Some of his students in recent years have been the children of people that he taught programming to in the 1980s.

Recent publications

  1. Krishnan, U.; Billerbeck, B.; Moffat, A.; Zobel, J. Abstraction of query auto completion logs for anonymity-preserving analysis. Information Retrieval Journal. Springer Science and Business Media LLC. 2019. DOI: 10.1007/s10791-019-09359-8
  2. Shane Culpepper, J.; Moffat, A.; Bennett, PN.; Lerman, K. Chairs' preface. WSDM 2019 - Proceedings of the 12th ACM International Conference on Web Search and Data Mining. 2019, pp. iii-iv.
  3. Pibiri, GE.; Petri, M.; Moffat, A. Fast dictionary-based compression for inverted indexes. Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining - WSDM '19. ACM Press. 2019, pp. 6-14. DOI: 10.1145/3289600.3290962
  4. Wicaksono, AF.; Moffat, A.; Zobel, J. Modeling user actions in job search. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer. 2019, Vol. 11437 LNCS, pp. 652-664. DOI: 10.1007/978-3-030-15712-8_42
  5. Salehi, B.; Spina, D.; Moffat, A.; Sadeghi, S.; Scholer, F.; Baldwin, T.; Cavedon, L.; Sanderson, M.; Wong, W.; Zobel, J. A living lab study of query amendment in job search. The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18. ACM. 2018, pp. 905-908. DOI: 10.1145/3209978.3210082
  6. Spina, D.; Maistro, M.; Ren, Y.; Sadeghi, S.; Wong, W.; Baldwin, T.; Cavedon, L.; Moffat, A.; Sanderson, M.; Scholer, F.; Zobel, J. A preliminary comparison of job, talent, and web search. CEUR Workshop Proceedings. CEUR Workshop Proceedings. 2018, Vol. 2140.
  7. Thomas, P.; Moffat, A.; Bailey, P.; Scholer, F.; Craswell, N. Better Effectiveness Metrics for SERPs, Cards, and Rankings. Proceedings of the 23rd Australasian Document Computing Symposium on ZZZ - ADCS '18. Association for Computing Machinery. 2018. DOI: 10.1145/3291992.3292002
  8. Petri, M.; Moffat, A. Compact inverted index storage using general-purpose compression libraries. Software: Practice and Experience. WILEY. 2018, Vol. 48, Issue 4, pp. 974-982. DOI: 10.1002/spe.2556
  9. Moffat, A. Computing Maximized Effectiveness Distance for Recall-Based Metrics. IEEE Transactions on Knowledge and Data Engineering. IEEE COMPUTER SOC. 2018, Vol. 30, Issue 1, pp. 198-203. DOI: 10.1109/TKDE.2017.2754371
  10. Moffat, A.; Petri, M. Computing the Cost of Compressed Data. . Springer International Publishing. 2018, pp. 1-5. DOI: 10.1007/978-3-319-63962-8_57-1
  11. Albahem, A.; Spina, D.; Scholer, F.; Moffat, A.; Cavedon, L. Desirable Properties for Diversity and Truncated Effectiveness Metrics. Proceedings of the 23rd Australasian Document Computing Symposium on ZZZ - ADCS '18. ASSOC COMPUTING MACHINERY. 2018. DOI: 10.1145/3291992.3291996
  12. Wicaksono, AF.; Moffat, A. Empirical Evidence for Search Effectiveness Models. Proceedings of the 27th ACM International Conference on Information and Knowledge Management - CIKM '18. Association for Computing Machinery. 2018, pp. 1571-1574. DOI: 10.1145/3269206.3269242
  13. Moffat, A.; Scholer, F.; Yang, Z. Estimating Measurement Uncertainty for Information Retrieval Effectiveness Metrics. Journal of Data and Information Quality. ASSOC COMPUTING MACHINERY. 2018, Vol. 10, Issue 3. DOI: 10.1145/3239572
  14. Wicaksono, AF.; Moffat, A. Exploring Interaction Patterns in Job Search. Proceedings of the 23rd Australasian Document Computing Symposium on ZZZ - ADCS '18. ACM. 2018. DOI: 10.1145/3291992.3292004
  15. Moffat, A.; Petri, M. Index compression using byte-ALIGNED ANS coding and two-dimensional contexts. Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining - WSDM '18. Association for Computing Machinery (ACM). 2018, Vol. 2018-Febuary, pp. 405-413. DOI: 10.1145/3159652.3159663
  16. Yang, Z.; Moffat, A.; Turpin, A. Pairwise Crowd Judgments: Preference, Absolute, and Ratio. Proceedings of the 23rd Australasian Document Computing Symposium on ZZZ - ADCS '18. ASSOC COMPUTING MACHINERY. 2018. DOI: 10.1145/3291992.3291995
  17. Gagie, T.; Moffat, A.; Navarro, G.; Cuadros-vargas, E. Preface. . 2018, Vol. 11147 LNCS, pp. v-.
  18. Moffat, A.; Wicaksono, AF. Users, Adaptivity, and Bad Abandonment. The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18. ACM Press. 2018, pp. 897-900. DOI: 10.1145/3209978.3210075
  19. Liao, K.; Moffat, A.; Petri, M.; Wirth, A. A cost model for long-term compressed data retention. Proceedings of the Tenth ACM International Conference on Web Search and Data Mining - WSDM '17. Association for Computing Machinery (ACM). 2017, pp. 241-249. DOI: 10.1145/3018661.3018738
  20. Krishnan, U.; Moffat, A.; Zobel, J. A taxonomy of query auto completion modes. Proceedings of the 22nd Australasian Document Computing Symposium on - ADCS 2017. ACM Press. 2017, Vol. 2017-December. DOI: 10.1145/3166072.3166081

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile