Dean Webb

500 total citations
13 papers, 227 citations indexed

About

Dean Webb is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Information Systems. According to data from OpenAlex, Dean Webb has authored 13 papers receiving a total of 227 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 3 papers in Electrical and Electronic Engineering and 2 papers in Information Systems. Recurrent topics in Dean Webb's work include Neural Networks and Applications (4 papers), Spam and Phishing Detection (2 papers) and Advanced Statistical Methods and Models (2 papers). Dean Webb is often cited by papers focused on Neural Networks and Applications (4 papers), Spam and Phishing Detection (2 papers) and Advanced Statistical Methods and Models (2 papers). Dean Webb collaborates with scholars based in Australia, Türkiye and United States. Dean Webb's co-authors include Adil Bagirov, Julien Ugon, John Yearwood, Moumita Ghosh, Gürkan Öztürk, Peter Vamplew, Bahadorreza Ofoghi, Musa Mammadov, Andrei Kelarev and Refail Kasımbeyli and has published in prestigious journals such as Pattern Recognition, American Journal of Health-System Pharmacy and Information Systems.

In The Last Decade

Dean Webb

13 papers receiving 206 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Dean Webb Australia 8 123 78 37 31 22 13 227
Joel Ratsaby Israel 8 220 1.8× 70 0.9× 14 0.4× 56 1.8× 17 0.8× 54 287
Muhammad Tanveer Hussain Pakistan 8 69 0.6× 44 0.6× 59 1.6× 30 1.0× 35 1.6× 27 260
Ali Shakiba Iran 11 73 0.6× 116 1.5× 33 0.9× 84 2.7× 15 0.7× 32 369
Moshe Ben-Bassat Israel 8 153 1.2× 35 0.4× 17 0.5× 32 1.0× 27 1.2× 26 364
David Vandevoorde United States 6 58 0.5× 20 0.3× 29 0.8× 26 0.8× 45 2.0× 8 195
Aryeh Kontorovich Israel 8 114 0.9× 23 0.3× 14 0.4× 21 0.7× 58 2.6× 34 245
S. Raja Balachandar India 9 39 0.3× 32 0.4× 24 0.6× 17 0.5× 38 1.7× 42 299
Bruno Costa Brazil 11 63 0.5× 27 0.3× 120 3.2× 16 0.5× 138 6.3× 17 277
Ragesh Jaiswal India 9 211 1.7× 38 0.5× 28 0.8× 129 4.2× 49 2.2× 27 316
Anastasios Zouzias Canada 9 211 1.7× 106 1.4× 9 0.2× 68 2.2× 50 2.3× 13 353

Countries citing papers authored by Dean Webb

Since Specialization
Citations

This map shows the geographic impact of Dean Webb'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 Dean Webb with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dean Webb more than expected).

Fields of papers citing papers by Dean Webb

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dean Webb. 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 Dean Webb. The network helps show where Dean Webb may publish in the future.

Co-authorship network of co-authors of Dean Webb

This figure shows the co-authorship network connecting the top 25 collaborators of Dean Webb. A scholar is included among the top collaborators of Dean Webb 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 Dean Webb. Dean Webb is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Vamplew, Peter, et al.. (2017). MORL-Glue: a benchmark suite for multi-objective reinforcement learning. Deakin Research Online (Deakin University). 5 indexed citations
2.
Bagirov, Adil, Julien Ugon, Dean Webb, Gürkan Öztürk, & Refail Kasımbeyli. (2011). A novel piecewise linear classifier based on polyhedral conic and max–min separabilities. Top. 21(1). 3–24. 21 indexed citations
3.
Yearwood, John, Musa Mammadov, & Dean Webb. (2011). Profiling phishing activity based on hyperlinks extracted from phishing emails. Social Network Analysis and Mining. 2(1). 5–16. 13 indexed citations
4.
Webb, Dean. (2011). Efficient piecewise linear classifiers and applications. FedUni ResearchOnline (Federation University Australia). 5 indexed citations
5.
Bagirov, Adil, Julien Ugon, & Dean Webb. (2010). An efficient algorithm for the incremental construction of a piecewise linear classifier. Information Systems. 36(4). 782–790. 17 indexed citations
6.
Bagirov, Adil, Julien Ugon, Dean Webb, & Bülent Karasözen. (2010). Classification through incremental max–min separability. Pattern Analysis and Applications. 14(2). 165–174. 9 indexed citations
7.
Bagirov, Adil, Julien Ugon, & Dean Webb. (2010). Fast modified global k-means algorithm for incremental cluster construction. Pattern Recognition. 44(4). 866–876. 94 indexed citations
8.
Bagirov, Adil, Julien Ugon, & Dean Webb. (2009). A new modified global k-means algorithm for clustering large data sets. FedUni ResearchOnline (Federation University Australia). 2 indexed citations
9.
Yearwood, John, et al.. (2009). Applying clustering and ensemble clustering approaches to phishing profiling. 25–34. 22 indexed citations
10.
Stergachis, Andy, et al.. (2007). Evaluation of a mass dispensing exercise in a Cities Readiness Initiative setting. American Journal of Health-System Pharmacy. 64(3). 285–293. 17 indexed citations
11.
Bagirov, Adil, Moumita Ghosh, & Dean Webb. (2006). A derivative-free method for linearly constrained nonsmooth optimization. Journal of Industrial and Management Optimization. 2(3). 319–338. 16 indexed citations
12.

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.

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