James Geller

187 papers receiving 1.8k citations

Peers

James Geller
Comparison fields: 5 of 108
  • Artificial Intelligence 1.5k
  • Health Information Management 134
  • Language and Linguistics 262
  • Molecular Biology 1.2k
  • Information Systems 295
Replace Pierre Zweigenbaum with:
Pierre Zweigenbaum France
Robert Gaizauskas United Kingdom
Sanda M. Harabagiu United States
Yue Wang China
Anna Rumshisky United States
Paloma Martı́nez Spain
Paul Kingsbury United States
Filip Ginter Finland
Judith L. Klavans United States
Tania Tudorache United States
James Geller relative to Pierre Zweigenbaum France Pierre Zweigenbaum's profile →
Citations per field
00.5×1.7×
Pierre Zweigenbaum · 1×
Citations per year

Countries citing papers authored by James Geller

Since Specialization
Citations

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

Fields of papers citing papers by James Geller

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 195 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201591
2 200682
3 201360
4 201444
5 201140
6 200335
7 201134
8 199134
9 201433
10
Auditing the UMLS for redundant classifications.
200231
11 200930
12 200226
13 199926
14 201725
15 201625
16 201524
17 200824
18 199924
19
Scalability of abstraction-network-based quality assurance to large SNOMED hierarchies.
201324
20 201523

About James Geller

James Geller is a scholar working on Artificial Intelligence, Language and Linguistics, Information Systems, Molecular Biology and Signal Processing, having authored 195 papers that have together received 1.9k indexed citations. Recurring topics across this work include Semantic Web and Ontologies (128 papers), Biomedical Text Mining and Ontologies (109 papers), Natural Language Processing Techniques (34 papers), Advanced Database Systems and Queries (19 papers), Service-Oriented Architecture and Web Services (18 papers), linguistics and terminology studies (18 papers), Topic Modeling (18 papers) and Data Management and Algorithms (13 papers). The work is most often cited by research in Artificial Intelligence (1.5k citations), Health Information Management (134 citations), Language and Linguistics (262 citations), Molecular Biology (1.2k citations) and Information Systems (295 citations). James Geller has collaborated with scholars based in United States, Germany and Taiwan. Frequent co-authors include Yehoshua Perl, Michael Halper, Soon Ae Chun, Christopher Ochs, Xiang Ji, Huanying Gu, Zhe He, Gai Elhanan, Yugyung Lee and Zhi Wei. Their work appears in journals such as Journal of Biomedical Informatics, Journal of the American Medical Informatics Association, Artificial Intelligence in Medicine, BMC Medical Informatics and Decision Making and Data & Knowledge Engineering.

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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