Michael Gertz

174 papers receiving 3.8k citations

Michael Gertz's Hit Papers

Mining email social networks 2006 · 374 citations
3740+6+13Years since publication100200300

Peers

Michael Gertz
Comparison fields: 5 of 164
  • Pharmacology 691
  • Signal Processing 601
  • Artificial Intelligence 1.6k
  • Information Systems 1.1k
  • Computer Science Applications 248
Replace Jaewoo Kang with:
Jaewoo Kang South Korea
Srinivasan Parthasarathy United States
James Noble New Zealand
Reda Alhajj Canada
Wen Zhang China
Yukun Chen China
Mario Cannataro Italy
Yong Liu China
David W. Cheung Hong Kong
Yue Yu China
Michael Gertz relative to Jaewoo Kang South Korea Jaewoo Kang's profile →
Citations per field
00.5×10×12.8×
Jaewoo Kang · 1×
Citations per year

Countries citing papers authored by Michael Gertz

Since Specialization
Citations

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

Fields of papers citing papers by Michael Gertz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 182 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Mining email social networks
Hit paper breakdown →
2006374
2 2010252
3
HeidelTime: High Quality Rule-Based Extraction and Normalization of Temporal Expressions
2010195
4 2013180
5 2008142
6 2012124
7 2004121
8 2012120
9 2003111
10 2011108
11 2007103
12 2007101
13 200891
14 201088
15
Temporal Information Retrieval: Challenges and Opportunities
201176
16 200972
17 200167
18 200760
19 200851
20 202246

About Michael Gertz

Michael Gertz is a scholar working on Artificial Intelligence, Computer Networks and Communications, Signal Processing, Information Systems and Computer Vision and Pattern Recognition, having authored 182 papers that have together received 4.1k indexed citations. Recurring topics across this work include Data Management and Algorithms (47 papers), Advanced Database Systems and Queries (41 papers), Semantic Web and Ontologies (38 papers), Natural Language Processing Techniques (29 papers), Topic Modeling (27 papers), Pharmacogenetics and Drug Metabolism (17 papers), Complex Network Analysis Techniques (17 papers) and Drug Transport and Resistance Mechanisms (13 papers). The work is most often cited by research in Pharmacology (691 citations), Signal Processing (601 citations), Artificial Intelligence (1.6k citations), Information Systems (1.1k citations) and Computer Science Applications (248 citations). Michael Gertz has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Jannik Strötgen, Aleksandra Galetin, Prémkumar Dévanbu, J. Brian Houston, Omar Alonso, J. Brian Houston, Christian Bird, Anand Swaminathan, Ricardo Baeza‐Yates and Hamed Abdelhaq. Their work appears in journals such as Drug Metabolism and Disposition, Language Resources and Evaluation, CPT Pharmacometrics & Systems Pharmacology, Journal of Computer Security and Distributed and Parallel Databases.

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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