STAFF PROFILE
Professor Falk Scholer
Position:
Professor
College / Portfolio:
STEM College
School / Department:
STEM|School of Computing Technologies
Phone:
+61399259831
Email:
falk.scholer@rmit.edu.au
Campus:
City Campus
Contact me about:
Research supervision,
Media comments
Dr Falk Scholer is a Professor in Information Retrieval, and the Deputy Director of the RMIT Centre for Information Discovery and Data Analytics (CIDDA)
Dr Falk Scholer is a research and teaching academic in the Discipline of Computer Science and IT, in the RMIT School of Science.
His research is in the area of information retrieval, with particular interests in:
- Web and enterprise search engines
- Evaluation of information retrieval systems
- User analytics
- Interactive search
- Relevance and user perceptions
- Fairness, Accountability, Transparency and Ethics of Computing
- Document summarisation
- Biomedical search
A list of Dr Scholer's publications is available on Google Scholar.
More information about his research and teaching is available at his personal website.
- Research supervision
- Teaching:
- Lecturer, Scripting Language Programming (COSC 1092/1093)
- Lecturer, Information Retrieval (ISYS 1078/1079)
PhD, MSc, BSc(Econ)
- Al Bahem, A.,Spina, D.,Scholer, F.,Cavedon, L. (2022). Component-based Analysis of Dynamic Search Performance In: ACM Transactions on Information Systems, 40, 1 - 47
- Tavakoli, L.,Zamani, H.,Scholer, F.,Croft, B.,Sanderson, M. (2022). Analyzing clarification in asynchronous information-seeking conversations In: Journal of the Association for Information Science and Technology, 73, 449 - 471
- Faggioli, G.,Zendel, O.,Culpepper, S.,Ferro, N.,Scholer, F. (2022). sMARE: a new paradigm to evaluate and understand query performance prediction methods In: Information Retrieval Journal, 25, 94 - 122
- Le, B.,Spina, D.,Scholer, F.,Chia, H. (2022). A Crowdsourcing Methodology to Measure Algorithmic Bias in Black-Box Systems: A Case Study with COVID-Related Searches In: Revised Selected Papers of the 3rd International Workshop on Advances in Bias and Fairness in Information Retrieval (BIAS 2022), Stavanger, Norway, 10 April 2022
- Khaokaew, Y.,Holcombe-James, I.,Saiedur Rahaman, M.,Trippas, J.,Spina, D.,Ren, Y.,Sanderson, M.,Scholer, F.,Salim, F. D., et al, . (2022). Imagining future digital assistants at work: A study of task management needs In: International Journal of Human Computer Studies, 168, 1 - 17
- Pathiyan Cherumanal, S.,Spina, D.,Scholer, F.,Croft, B. (2021). Evaluating Fairness in Argument Retrieval In: Proceedings of the 30th ACM International Conference on Information & Knowledge Management (CIKM 2021), Queensland, Australia, 1-5 November 2021
- Roitero, K.,Maddalena, E.,Mizzaro, S.,Scholer, F. (2021). On the effect of relevance scales in crowdsourcing relevance assessments for Information Retrieval evaluation In: Information Processing and Management, 58, 1 - 23
- Zendel, O.,Culpepper, S.,Scholer, F. (2021). Is Query Performance Prediction With Multiple Query Variations Harder Than Topic Performance Prediction? In: SIGIR '21: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, Virtual Event Canada, 11-15 July 2021
- Faggioli, G.,Zendel, O.,Culpepper, J.,Ferro, N.,Scholer, F. (2021). An Enhanced Evaluation Framework for Query Performance Prediction In: Advances in Information Retrieval - 43rd European Conference on IR Research, Virtual, Mar 28-Apr 1 2021
- Steiner, M.,Spina, D.,Scholer, F.,Cavedon, L. (2021). Crowdsourcing Backstories for Complex Task-Based Search In: Proceedings of the 25th Australasian Document Computing Symposium (ADCS 2021), Virtual Event, Australia, 9 December 2021
- New approaches to interactive sessional search for complex tasks. Funded by: ARC Discovery Projects 2019 from (2019 to 2022)
- Archistar Innovation Connection Grant. Funded by: Archistar Pty Ltd Contract from (2019 to 2020)
- Finding answers for complex questions. Funded by: ARC Discovery Projects 2018 from (2018 to 2022)
- A cyber physical and socially aware personal assistant. Funded by: Microsoft Corporation (USA) - research grant 2018 from (2018 to 2020)
- User-Adaptive Search and Evaluation for Complex Information-Seeking Tasks. Funded by: ARC Linkage Grant 2015 Round 1 from (2016 to 2019)
Note: Supervision projects since 2004
21 PhD Completions and 1 Masters by Research Completions8 PhD Current Supervisions
Information retrieval; search engines; past queries and query log analysis; query refinement and expansion; document summarisation; retrieval models; document surrogates; efficient indexing and data structures.