Michael Oakes

3.1k citations
111 papers · 2.0k · h-index 19

Impact in

Papers in

    • Natural Language Processing Techniques 33
    • Semantic Web and Ontologies 19
    • Topic Modeling 13
    • Text and Document Classification Technologies 12
    • Authorship Attribution and Profiling 9
    • Web Data Mining and Analysis 8

Michael Oakes

105 papers receiving 1.8k citations

Peers

Michael Oakes
Comparison fields: 5 of 160
  • Transportation 177
  • Artificial Intelligence 555
  • Pulmonary and Respiratory Medicine 367
  • Speech and Hearing 62
  • Cardiology and Cardiovascular Medicine 197
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Michael Oakes relative to Kenneth W. Goodman United States Kenneth W. Goodman's profile →
Citations per field
00.5×9.8×
Kenneth W. Goodman · 1×
Citations per year

Countries citing papers authored by Michael Oakes

Since Specialization
Citations

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

Fields of papers citing papers by Michael Oakes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 111 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1984239
2 2011200
3 2009182
4 2006159
5 2003152
6 200975
7 201969
8 198565
9 201064
10 200656
11 200654
12 202036
13 200135
14 200026
15
Literature Review of Cross Language Information Retrieval.
200526
16 201325
17 201225
18 201220
19
Abnormal laboratory test values during ceftriaxone therapy.
198419
20 201518

About Michael Oakes

Michael Oakes is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Language and Linguistics and Molecular Biology, having authored 111 papers that have together received 2.0k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (33 papers), Semantic Web and Ontologies (19 papers), Topic Modeling (13 papers), Image Retrieval and Classification Techniques (13 papers), Text and Document Classification Technologies (12 papers), Authorship Attribution and Profiling (9 papers), Web Data Mining and Analysis (8 papers) and Advanced Image and Video Retrieval Techniques (7 papers). The work is most often cited by research in Transportation (177 citations), Artificial Intelligence (555 citations), Pulmonary and Respiratory Medicine (367 citations), Speech and Hearing (62 citations) and Cardiology and Cardiovascular Medicine (197 citations). Michael Oakes has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include John Tait, Eric Henderson, James A. Lake, Megan Clark, Christopher Stokoe, Ann Forsyth, Maria Dilleen, Ghazwan Butrous, David Wessel and Kristen Day. Their work appears in journals such as Proceedings of the National Academy of Sciences, Lecture notes in computer science, Circulation, Blood and CHEST Journal.

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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