Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A survey on the adoption of blockchain in IoT: challenges and solutions
2021229 citationsAndrew Stranieri, Venki Balasubramanian et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
Countries citing papers authored by Andrew Stranieri
Since
Specialization
Citations
This map shows the geographic impact of Andrew Stranieri's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Andrew Stranieri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Stranieri more than expected).
Fields of papers citing papers by Andrew Stranieri
This network shows the impact of papers produced by Andrew Stranieri. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Andrew Stranieri. The network helps show where Andrew Stranieri may publish in the future.
Co-authorship network of co-authors of Andrew Stranieri
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Stranieri.
A scholar is included among the top collaborators of Andrew Stranieri based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Andrew Stranieri. Andrew Stranieri is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Stranieri, Andrew, et al.. (2017). Deriving Value from Health 2.0: A Study of Social Media Use in Australian Healthcare Organizations. Journal of the Association for Information Systems. 283.3 indexed citations
7.
McCullough, Michael, Andrew Stranieri, R. D. COLLMANN, et al.. (2014). Field testing of remote teledentistry technology. Minerva Access (University of Melbourne). 23–28.3 indexed citations
8.
Mariño, Rodrigo, MS Hopcraft, Utsana Tonmukayakul, et al.. (2014). Teleconsultation/telediagnosis using teledentistry technology: a pilot feasibility study. Deakin Research Online (Deakin University). 6. 291–299.24 indexed citations
9.
Jelinek, Herbert F., Daswin De Silva, Frada Burstein, et al.. (2013). Association of ankle brachial pressure index with heart rate variability in a rural screening clinic. eCite Digital Repository (University of Tasmania). 40. 755–758.1 indexed citations
10.
Vamplew, Peter, Andrew Stranieri, Kok‐Leong Ong, Peter Christen, & Paul Kennedy. (2011). AusDM 11 : Proceedings of the Ninth Australasian Data Mining Conference.
11.
Quinn, Anthony, Andrew Stranieri, John Yearwood, Gaudenz Hafen, & Herbert F. Jelinek. (2008). AWSum: Combining classification with knowledge aquisition. SERVAL (Université de Lausanne). 2(2). 199–214.1 indexed citations
12.
Quinn, Anthony, Andrew Stranieri, & John Yearwood. (2007). Classification for accuracy and insight: a weighted sum approach. FedUni ResearchOnline (Federation University Australia). 203–208.8 indexed citations
13.
Yearwood, John & Andrew Stranieri. (2007). Narrative-based Interactive Learning Environments from Modelling Reasoning. Educational Technology & Society. 10(3). 192–208.4 indexed citations
14.
Stranieri, Andrew, et al.. (2007). An argument structure abstraction for bayesian belief networks: just outcomes in on-line dispute resolution. FedUni ResearchOnline (Federation University Australia). 35–40.2 indexed citations
15.
Mishra, Vivek, et al.. (2006). Knowledge based regulation of statistical databases. FedUni ResearchOnline (Federation University Australia).1 indexed citations
16.
Sourdin, Tania, et al.. (2005). Supporting discretionary decision-making with information technology: a case study in the criminal sentencing jurisdiction. Victoria University Research Repository (Victoria University).8 indexed citations
17.
Governatori, Guido & Andrew Stranieri. (2001). Towards the Application of Association Rules for Defeasible Rule Discovery. 63–75.15 indexed citations
Stranieri, Andrew & John Zeleznikow. (1998). Split up: the use of an argument based knowledge representation to meet expectations of different user for discretionary decision making. National Conference on Artificial Intelligence. 1146–1151.6 indexed citations
20.
Zeleznikow, John & Andrew Stranieri. (1997). Modelling discretion in the Split Up system. Journal of the Association for Information Systems. 31.4 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.