Ira Monarch

32 papers receiving 1.2k citations

Peers

Ira Monarch
Comparison fields: 5 of 129
  • Management of Technology and Innovation 158
  • Human-Computer Interaction 90
  • Statistics, Probability and Uncertainty 105
  • Computer Science Applications 76
  • Management Information Systems 104
Replace Suresh Konda with:
Suresh Konda United States
Yuen‐Hsien Tseng Taiwan
Ken Eason United Kingdom
William Remus United States
Fred Collopy United States
Murugan Anandarajan United States
Jae Young Choi South Korea
Yuqiang Feng China
Sean B. Eom United States
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Citations per year

Countries citing papers authored by Ira Monarch

Since Specialization
Citations

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

Fields of papers citing papers by Ira Monarch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Ira Monarch, 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 Ira Monarch Line = papers co-authored together Ira Monarch links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1998309
2 1998240
3 1992196
4 199692
5 200382
6 199282
7
Automatic indexing using selective NLP and first-order thesauri
199154
8 199343
9 198738
10 199136
11 199325
12 201520
13 199119
14 20037
15 20026
16 19944
17 20024
18 20133
19 20173
20
Knowledge Networks: A Case Study in Establishing a Domain of Software Engineering Knowledge
20003

About Ira Monarch

Ira Monarch is a scholar working on Information Systems, Artificial Intelligence, Computer Science Applications, Mechanical Engineering and Human-Computer Interaction, having authored 34 papers that have together received 1.3k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (7 papers), Software Engineering Research (6 papers), Design Education and Practice (5 papers), Natural Language Processing Techniques (5 papers), Open Source Software Innovations (5 papers), Software Engineering Techniques and Practices (5 papers), Usability and User Interface Design (5 papers) and Scientific Computing and Data Management (3 papers). The work is most often cited by research in Management of Technology and Innovation (158 citations), Human-Computer Interaction (90 citations), Statistics, Probability and Uncertainty (105 citations), Computer Science Applications (76 citations) and Management Information Systems (104 citations). Ira Monarch has collaborated with scholars based in United States, Australia and Italy. Frequent co-authors include Suresh Konda, Neal S. Coulter, Eswaran Subrahmanian, Dewey I. Dykstra, C. Franklin Boyle, Yoram Reich, David A. Evans, Philip Sargent, Arthur W. Westerberg and William Hersh. Their work appears in journals such as Design Studies, Medical Decision Making, Journal of the Association for Information Systems, Management Learning and Science Education.

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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