Simon Razniewski

1.1k citations
68 papers · 517 · h-index 13

Impact in

Papers in

Simon Razniewski

62 papers receiving 499 citations

Peers

Simon Razniewski
Comparison fields: 5 of 56
  • Management Science and Operations Research 159
  • Artificial Intelligence 417
  • Information Systems 115
  • Communication 32
  • Signal Processing 36
Replace Saeedeh Shekarpour with:
Saeedeh Shekarpour Germany
Pavan Kapanipathi United States
You Wu United States
Ndapa Nakashole United States
Cane Wing-ki Leung Hong Kong
Taylor Cassidy United States
Ricardo Usbeck Germany
Sheila Kinsella Ireland
Edward Benson United States
David Ruiz Spain
Simon Razniewski relative to Saeedeh Shekarpour Germany Saeedeh Shekarpour's profile →
Citations per field
00.5×2.5×
Saeedeh Shekarpour · 1×
Citations per year

Countries citing papers authored by Simon Razniewski

Since Specialization
Citations

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

Fields of papers citing papers by Simon Razniewski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 68 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202065
2 201137
3 201834
4 201731
5 201327
6 201526
7 202120
8 202318
9 201816
10 201616
11
Managing and Consuming Completeness Information for Wikidata Using COOL-WD.
201613
12 202112
13 201712
14 201710
15 201810
16 20119
17 20179
18 20168
19 20218
20 20198

About Simon Razniewski

Simon Razniewski is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 68 papers that have together received 517 indexed citations. Recurring topics across this work include Topic Modeling (36 papers), Semantic Web and Ontologies (25 papers), Natural Language Processing Techniques (23 papers), Data Quality and Management (20 papers), Advanced Database Systems and Queries (14 papers), Advanced Graph Neural Networks (11 papers), Web Data Mining and Analysis (8 papers) and Logic, Reasoning, and Knowledge (7 papers). The work is most often cited by research in Management Science and Operations Research (159 citations), Artificial Intelligence (417 citations), Information Systems (115 citations), Communication (32 citations) and Signal Processing (36 citations). Simon Razniewski has collaborated with scholars based in Germany, Italy and France. Frequent co-authors include Werner Nutt, Gerhard Weikum, Fabian M. Suchanek, Paramita Mirza, Aparna S. Varde, Giuseppe Pirrò, Niket Tandon, Divesh Srivastava, Flip Korn and Daria Stepanova. Their work appears in journals such as Proceedings of the VLDB Endowment, Lecture notes in computer science, Transactions of the Association for Computational Linguistics, Semantic Web and Journal of Web Semantics.

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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