Marcin Sydow

763 citations
32 papers · 397 · h-index 11

Impact in

Papers in

Marcin Sydow

32 papers receiving 370 citations

Peers

Marcin Sydow
Comparison fields: 5 of 55
  • Artificial Intelligence 245
  • Information Systems 164
  • Management Science and Operations Research 81
  • Signal Processing 68
  • Communication 26
Replace Minsung Hong with:
Minsung Hong South Korea
Marie-Aude Aufaure France
Jalel Akaichi Tunisia
Silviu Maniu France
Jer Hayes Ireland
Xing Zhao China
Véronique Malaisé Netherlands
Riccardo Ortale Italy
P. Dolan United States
Gianni Costa Italy
Marcin Sydow relative to Minsung Hong South Korea Minsung Hong's profile →
Citations per field
00.5×4.9×
Minsung Hong · 1×
Citations per year

Countries citing papers authored by Marcin Sydow

Since Specialization
Citations

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

Fields of papers citing papers by Marcin Sydow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Marcin Sydow, 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 Marcin Sydow Line = papers co-authored together Marcin Sydow links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201461
2 200952
3 200851
4 201339
5 200936
6 200920
7 200416
8 201416
9 201316
10 201611
11 201710
12 20188
13 20077
14 20107
15 20086
16 20216
17 20156
18
Application of ant-colony optimisation to compute diversified entity summarisation on semantic knowledge graphs
20135
19 20153
20
“CRAWL.PL” Measuring Statistical and Structural Properties of the Polish Web : Technical Report
20072

About Marcin Sydow

Marcin Sydow is a scholar working on Artificial Intelligence, Information Systems, Management Science and Operations Research, Statistical and Nonlinear Physics and Signal Processing, having authored 32 papers that have together received 397 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (10 papers), Semantic Web and Ontologies (8 papers), Data Quality and Management (8 papers), Topic Modeling (7 papers), Authorship Attribution and Profiling (4 papers), Complex Network Analysis Techniques (4 papers), Web visibility and informetrics (4 papers) and Data Management and Algorithms (3 papers). The work is most often cited by research in Artificial Intelligence (245 citations), Information Systems (164 citations), Management Science and Operations Research (81 citations), Signal Processing (68 citations) and Communication (26 citations). Marcin Sydow has collaborated with scholars based in Poland, Germany and Italy. Frequent co-authors include Ralf Schenkel, Jakub Piskorski, Dawid Weiss, Érico N. de Souza, Stan Matwin, Adam Wierzbicki, Shady Elbassuoni, Maya Ramanath, Gerhard Weikum and Paweł Teisseyre. Their work appears in journals such as Journal of Intelligent Information Systems, Information Retrieval, PLoS ONE, Fundamenta Informaticae and SHILAP Revista de lepidopterología.

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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