Aaron Ceglar

453 citations
14 papers · 221 indexed · h-index 5

Impact in

Papers in

Aaron Ceglar

13 papers receiving 194 citations

Peers

Aaron Ceglar
Comparison fields: 5 of 43
  • Information Systems 168
  • Signal Processing 75
  • Computational Theory and Mathematics 101
  • Artificial Intelligence 101
  • Computer Science Applications 11
Replace Antonio Gomariz with:
Antonio Gomariz Spain
Ted Gueniche Canada
Vikram Goyal India
Silvia Calegari Italy
Mafruz Zaman Ashrafi Australia
Yu-Chiang Li Taiwan
Robert J. Hilderman Canada
Nazareno Aguirre Argentina
Jenny Y. Chiang Canada
Dietmar Seipel Germany
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Citations per field
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Citations per year

Countries citing papers authored by Aaron Ceglar

Since Specialization
Citations

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

Fields of papers citing papers by Aaron Ceglar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 12 scholars most cited alongside Aaron Ceglar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Aaron Ceglar Line = papers co-authored together Aaron Ceglar links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 20191
2 20182
3
Interaction Challenges for the Dynamic Construction of Partially-Ordered Sets.
20142
4 20141
5 20131
6
Mining Medical Administrative Data --The PKB Suite
20100
7
Discovering itemset interactions
20091
8
Incremental Association Mining using a Closed-Set Lattice
20084
9 200820
10
CURIO: a fast outlier and outlier cluster detection algorithm for large datasets
20077
11 20073
12 2006171
13 20047
14
From rule visualisation to guided knowledge discovery
20031

About Aaron Ceglar

Aaron Ceglar is a scholar working on Computational Theory and Mathematics, Signal Processing, Information Systems, Artificial Intelligence and Management Science and Operations Research, having authored 14 papers that have together received 221 indexed citations. Recurring topics across this work include Rough Sets and Fuzzy Logic (7 papers), Data Mining Algorithms and Applications (6 papers), Imbalanced Data Classification Techniques (3 papers), Data Management and Algorithms (3 papers), Topic Modeling (2 papers), Data Quality and Management (2 papers), Innovative Teaching and Learning Methods (1 paper) and Information Retrieval and Search Behavior (1 paper). The work is most often cited by research in Information Systems (168 citations), Signal Processing (75 citations), Computational Theory and Mathematics (101 citations), Artificial Intelligence (101 citations) and Computer Science Applications (11 citations). Aaron Ceglar has collaborated with scholars based in Australia, Germany and United States. Frequent co-authors include John F. Roddick, Myra Spiliopoulou, David Powers, Paul Calder, Tim Pattison, Kathryn Parsons, Marcus Butavicius, Simon Dennis, Carl Mooney and Richard Leibbrandt. Their work appears in journals such as International Journal of Human-Computer Interaction, ACM Computing Surveys, Knowledge and Information Systems, International Journal of Business Intelligence and Data Mining and ACM SIGKDD Explorations Newsletter.

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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