Darrell Ray Toothman

505 citations
9 papers · 362 indexed · h-index 7

Impact in

Papers in

Darrell Ray Toothman

7 papers receiving 317 citations

Peers

Darrell Ray Toothman
Comparison fields: 5 of 88
  • Management of Technology and Innovation 54
  • Statistics, Probability and Uncertainty 54
  • Management Science and Operations Research 75
  • Management Information Systems 38
  • Artificial Intelligence 118
Replace Henry J. Eberhart with:
Henry J. Eberhart United States
James A. Humenik United States
Edgar Schiebel Austria
Jos Winnink Netherlands
Tamy Chambers United States
Bernard Dousset France
Diana Lucio‐Arias Colombia
Yoo Kyung Jeong South Korea
Liying Yang China
Clara Calero‐Medina Netherlands
Darrell Ray Toothman relative to Henry J. Eberhart United States Henry J. Eberhart's profile →
Citations per field
00.5×1.5×
Henry J. Eberhart · 1×
Citations per year

Countries citing papers authored by Darrell Ray Toothman

Since Specialization
Citations

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

Fields of papers citing papers by Darrell Ray Toothman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Darrell Ray Toothman. 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 Darrell Ray Toothman. The network helps show where Darrell Ray Toothman may publish in the future.

Co-authorship network

The 5 scholars most cited alongside Darrell Ray Toothman, 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 Darrell Ray Toothman Line = papers co-authored together Darrell Ray Toothman links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1
Science and Technology Text Mining: Near-Earth Space
20031
2 2001117
3 200026
4 20000
5 199923
6 199932
7 199943
8 199856
9 199764

About Darrell Ray Toothman

Darrell Ray Toothman is a scholar working on Management Science and Operations Research, Physical and Theoretical Chemistry, Artificial Intelligence, Geography, Planning and Development and Information Systems and Management, having authored 9 papers that have together received 362 indexed citations. Recurring topics across this work include Data Quality and Management (6 papers), Geochemistry and Geologic Mapping (4 papers), Semantic Web and Ontologies (4 papers), Web Data Mining and Analysis (2 papers), History and advancements in chemistry (2 papers), Geographic Information Systems Studies (1 paper), Information Retrieval and Search Behavior (1 paper) and Biomedical Text Mining and Ontologies (1 paper). The work is most often cited by research in Management of Technology and Innovation (54 citations), Statistics, Probability and Uncertainty (54 citations), Management Science and Operations Research (75 citations), Management Information Systems (38 citations) and Artificial Intelligence (118 citations). Darrell Ray Toothman has collaborated with scholars based in United States and Hungary. Frequent co-authors include Ronald N. Kostoff, Henry J. Eberhart, James A. Humenik, Tibor Braun and A. Schubert. Their work appears in journals such as Journal of Aircraft, Information Processing & Management, Journal of Information Science, Technological Forecasting and Social Change and Defense Technical Information Center (DTIC).

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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