Michael B. Spring

1.7k citations
66 papers · 1.2k indexed · h-index 16

Impact in

Papers in

Michael B. Spring

60 papers receiving 1.1k citations

Peers

Michael B. Spring
Comparison fields: 5 of 124
  • Applied Psychology 279
  • Information Systems 228
  • Artificial Intelligence 305
  • Computer Science Applications 51
  • Experimental and Cognitive Psychology 119
Replace Yin Leng Theng with:
Yin Leng Theng Singapore
Didi Surian Australia
Arfan Ahmed Qatar
Edward Meinert United Kingdom
Sofía Ouhbi United Arab Emirates
Jina Huh United States
Allan S. Cohen United States
Dari Alhuwail Kuwait
Alexander Markowetz Germany
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Michael B. Spring relative to Yin Leng Theng Singapore Yin Leng Theng's profile →
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Citations per year

Countries citing papers authored by Michael B. Spring

Since Specialization
Citations

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

Fields of papers citing papers by Michael B. Spring

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael B. Spring. 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 Michael B. Spring. The network helps show where Michael B. Spring may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993172
2 2007113
3 2005100
4 201794
5 201693
6 201383
7 200568
8 200964
9
A Harmony based Adaptive Ontology Mapping Approach
200830
10 201726
11 201022
12 201119
13 200719
14 200817
15 200316
16 199915
17 201314
18 199713
19
Adaptive, Engaging, and Explanatory Visualization in a C Programming Course
200412
20 200912

About Michael B. Spring

Michael B. Spring is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Oncology and Applied Psychology, having authored 66 papers that have together received 1.2k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (20 papers), Service-Oriented Architecture and Web Services (9 papers), Web Data Mining and Analysis (9 papers), Digital Mental Health Interventions (6 papers), Cancer survivorship and care (6 papers), Advanced Database Systems and Queries (5 papers), Biomedical Text Mining and Ontologies (5 papers) and Open Source Software Innovations (4 papers). The work is most often cited by research in Applied Psychology (279 citations), Information Systems (228 citations), Artificial Intelligence (305 citations), Computer Science Applications (51 citations) and Experimental and Cognitive Psychology (119 citations). Michael B. Spring has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Armando J. Rotondi, Ming Mao, Yefei Peng, James Williams, Kai A. Olsen, Robert R. Korfhage, Gretchen L. Haas, Carol Anderson, Christina E. Newhill and Rohan Ganguli. Their work appears in journals such as Journal of Clinical Oncology, Computer Standards & Interfaces, Computer, Cancer and Schizophrenia Bulletin.

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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