Guus Schreiber

4.8k total citations
97 papers, 2.1k citations indexed

About

Guus Schreiber is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Guus Schreiber has authored 97 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Artificial Intelligence, 30 papers in Information Systems and 18 papers in Computer Vision and Pattern Recognition. Recurrent topics in Guus Schreiber's work include Semantic Web and Ontologies (52 papers), Natural Language Processing Techniques (16 papers) and Biomedical Text Mining and Ontologies (13 papers). Guus Schreiber is often cited by papers focused on Semantic Web and Ontologies (52 papers), Natural Language Processing Techniques (16 papers) and Biomedical Text Mining and Ontologies (13 papers). Guus Schreiber collaborates with scholars based in Netherlands, United Kingdom and United States. Guus Schreiber's co-authors include Bob Wielinga, Walter Van de Velde, Hans Akkermans, Laura Hollink, Robert de Hoog, Lora Aroyo, Joost Breuker, Willem Robert van Hage, Véronique Malaisé and Roxane Segers and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Multimedia and International Journal of Human-Computer Studies.

In The Last Decade

Guus Schreiber

90 papers receiving 1.9k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Guus Schreiber Netherlands 22 1.3k 622 475 228 204 97 2.1k
Lynn Andrea Stein United States 18 1.5k 1.1× 862 1.4× 236 0.5× 508 2.2× 179 0.9× 59 2.3k
A.T. Schreiber Netherlands 16 2.1k 1.6× 1.2k 1.9× 512 1.1× 569 2.5× 396 1.9× 42 2.9k
Michael Granitzer Germany 20 1.2k 0.9× 561 0.9× 432 0.9× 130 0.6× 72 0.4× 167 1.8k
Marta Sabou Austria 26 1.4k 1.1× 939 1.5× 135 0.3× 295 1.3× 267 1.3× 112 1.9k
Ruben Verborgh Belgium 18 872 0.7× 617 1.0× 228 0.5× 381 1.7× 150 0.7× 184 1.5k
Rafael Valencia-Garcı́a Spain 26 1.3k 1.0× 1.1k 1.7× 197 0.4× 256 1.1× 145 0.7× 131 2.2k
Eero Hyvönen Finland 20 1.4k 1.0× 757 1.2× 393 0.8× 343 1.5× 199 1.0× 223 2.0k
Kuansan Wang United States 23 2.0k 1.5× 960 1.5× 502 1.1× 207 0.9× 276 1.4× 65 3.1k
Costas Vassilakis Greece 21 648 0.5× 654 1.1× 488 1.0× 382 1.7× 117 0.6× 162 1.8k
Jaimie Murdock United States 16 1.5k 1.1× 473 0.8× 250 0.5× 217 1.0× 126 0.6× 46 2.0k

Countries citing papers authored by Guus Schreiber

Since Specialization
Citations

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

Fields of papers citing papers by Guus Schreiber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guus Schreiber

This figure shows the co-authorship network connecting the top 25 collaborators of Guus Schreiber. A scholar is included among the top collaborators of Guus Schreiber based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Guus Schreiber. Guus Schreiber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Fokkens, Antske, et al.. (2017). BiographyNet: Extracting Relations between People and Events. VU Research Portal. 193–227. 7 indexed citations
2.
Wielemaker, Jan, et al.. (2017). How Plausible is Automatic Annotation of Scientific Spreadsheets. 2065. 26–31.
3.
Hildebrand, Michiel, et al.. (2017). Topical Video Search: Analysing Video Concept Annotation through Crowdsourcing Games. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 4(1). 47–70. 1 indexed citations
4.
Ossenbruggen, Jacco van, et al.. (2014). INVENiT: exploring cultural heritage collections while adding annotations. Data Archiving and Networked Services (DANS). 1279. 95–99.
5.
Fokkens, Antske, et al.. (2014). BiographyNet: Methodological Issues when NLP supports historical research. Language Resources and Evaluation. 3728–3735. 14 indexed citations
6.
Sandberg, Jacobijn, et al.. (2014). Validating Ontologies for Question Generation. UvA-DARE (University of Amsterdam).
7.
Boer, Victor de, Jan Wielemaker, Michiel Hildebrand, et al.. (2013). Amsterdam Museum Linked Open Data. Semantic Web. 4(3). 237–243. 20 indexed citations
8.
Ceolin, Davide, Willem Robert van Hage, Wan Fokkink, & Guus Schreiber. (2011). Estimating uncertainty of categorical web data. Data Archiving and Networked Services (DANS). 778. 15–26. 3 indexed citations
9.
Presutti, Valentina, et al.. (2011). Extracting Core Knowledge from Linked Data. Data Archiving and Networked Services (DANS). 782. 37–48. 19 indexed citations
10.
Ruotsalo, Tuukka, Lora Aroyo, & Guus Schreiber. (2009). Knowledge-Based Linguistic Annotation of Digital Cultural Heritage Collections. IEEE Intelligent Systems. 24(2). 64–75. 23 indexed citations
11.
Vries, Geert de, et al.. (2008). Semi-Automatic Ontology Extension in the Maritime Domain. UvA-DARE (University of Amsterdam). 20. 265–272. 5 indexed citations
12.
Hage, Willem Robert van, et al.. (2008). Relevance-based evaluation of alignment approaches: The OAEI2007 food task revisited. Data Archiving and Networked Services (DANS). 431. 234–238. 1 indexed citations
13.
Pan, Jeff Z., Ian Horrocks, & Guus Schreiber. (2005). OWL FA: A Metamodeling Extension of OWL DL.. Data Archiving and Networked Services (DANS). 25 indexed citations
14.
Fensel, Dieter, Enrico Motta, V. Richard Benjamins, et al.. (1999). The Unified Problem-Solving Method Development Language. Ecological Entomology. 7 indexed citations
15.
Post, W. M., et al.. (1997). Organizational modeling in CommonKADS: the emergency medical service. IEEE Expert. 12(6). 46–52. 8 indexed citations
16.
Velde, Walter Van de & Guus Schreiber. (1996). The Future of Knowledge Acquisition: a European Perspective. IEEE Intelligent Systems. 11(2). 64–66. 4 indexed citations
17.
Heijst, GertJan van, W. M. Post, & Guus Schreiber. (1994). Knowledge based integration of representation formalisms. UvA-DARE (University of Amsterdam). 319–323. 1 indexed citations
18.
Schreiber, Guus, Bob Wielinga, & Joost Breuker. (1993). KADS : a principled approach to knowledge-based system development. Academic Press eBooks. 187 indexed citations
19.
Vinkhuyzen, Erik, Angi Voß, Hans Akkermans, et al.. (1991). A Conceptual Modelling Framework for Knowledge-level Reflection. AI Communications. 4(2-3). 74–87. 14 indexed citations
20.
Breuker, Joost, et al.. (1988). StatCons: knowledge acquisition in a complex domain. European Conference on Artificial Intelligence. 100–105. 2 indexed citations

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Lynn Andrea Stein Breakdown of academic impact, for papers by A.T. Schreiber Breakdown of academic impact, for papers by Michael Granitzer Breakdown of academic impact, for papers by Marta Sabou Breakdown of academic impact, for papers by Ruben Verborgh Breakdown of academic impact, for papers by Rafael Valencia-Garcı́a Breakdown of academic impact, for papers by Eero Hyvönen Breakdown of academic impact, for papers by Kuansan Wang Breakdown of academic impact, for papers by Costas Vassilakis Breakdown of academic impact, for papers by Jaimie Murdock
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