Michael Cochez

3.8k citations
47 papers · 1.7k · 1 hit paper · h-index 16

Impact in

Papers in

Michael Cochez

44 papers receiving 1.6k citations

Michael Cochez's Hit Papers

Knowledge Graphs 2021 · 690 citations
6900+1+3Years since publication200400600

Peers

Michael Cochez
Comparison fields: 5 of 153
  • Health Informatics 71
  • Artificial Intelligence 905
  • Management Science and Operations Research 171
  • Computational Theory and Mathematics 172
  • Information Systems 237
Replace Chen Lin with:
Chen Lin China
Alberto Lavelli Italy
Zeyar Aung United Arab Emirates
Daniel Golovin United States
Yun Xiong China
Alexey Tsymbal Finland
Fan Jiang China
Zongda Wu China
Pengtao Xie United States
Michael Cochez relative to Chen Lin China Chen Lin's profile →
Citations per field
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Citations per year

Countries citing papers authored by Michael Cochez

Since Specialization
Citations

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

Fields of papers citing papers by Michael Cochez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Knowledge Graphs
Hit paper breakdown →
2021690
2 2019186
3 2019105
4 202098
5 202386
6 202052
7 202152
8 202252
9 201747
10 202144
11
DeepCOVIDExplainer: Explainable COVID-19 Predictions Based on Chest X-ray Images
202043
12 201727
13 201523
14 201822
15 202316
16
Complex Query Answering with Neural Link Predictors
202116
17 201915
18 201515
19 202010
20 20139

About Michael Cochez

Michael Cochez is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 47 papers that have together received 1.7k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (14 papers), Topic Modeling (12 papers), Semantic Web and Ontologies (7 papers), Graph Theory and Algorithms (5 papers), Data Quality and Management (3 papers), Domain Adaptation and Few-Shot Learning (3 papers), Algorithms and Data Compression (3 papers) and Bioinformatics and Genomic Networks (3 papers). The work is most often cited by research in Health Informatics (71 citations), Artificial Intelligence (905 citations), Management Science and Operations Research (171 citations), Computational Theory and Mathematics (172 citations) and Information Systems (237 citations). Michael Cochez has collaborated with scholars based in Germany, Netherlands and Finland. Frequent co-authors include Stefan Decker, Md. Rezaul Karim, Oya Beyan, Dietrich Rebholz‐Schuhmann, Axel-Cyrille Ngonga Ngomo, Anisa Rula, Sabrina Kirrane, Sabbir M. Rashid, Juan Sequeda and Gerard de Melo. Their work appears in journals such as Briefings in Bioinformatics, Semantic Web, Journal of Biomedical Semantics, Information Sciences and Knowledge and Information Systems.

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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