Dolf Trieschnigg

2.0k total citations
44 papers, 654 citations indexed

About

Dolf Trieschnigg is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Dolf Trieschnigg has authored 44 papers receiving a total of 654 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 16 papers in Information Systems and 9 papers in Molecular Biology. Recurrent topics in Dolf Trieschnigg's work include Web Data Mining and Analysis (13 papers), Topic Modeling (11 papers) and Biomedical Text Mining and Ontologies (9 papers). Dolf Trieschnigg is often cited by papers focused on Web Data Mining and Analysis (13 papers), Topic Modeling (11 papers) and Biomedical Text Mining and Ontologies (9 papers). Dolf Trieschnigg collaborates with scholars based in Netherlands, Belgium and United States. Dolf Trieschnigg's co-authors include Franciska de Jong, Dong Nguyen, Wessel Kraaij, Maral Dadvar, T. Meder, Djoerd Hiemstra, Roeland Ordelman, Thomas Demeester, Mariët Theune and Edgar Meij and has published in prestigious journals such as Bioinformatics, Information Processing & Management and ACM Transactions on Information Systems.

In The Last Decade

Dolf Trieschnigg

42 papers receiving 616 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dolf Trieschnigg Netherlands 14 472 216 123 91 86 44 654
Prasenjit Majumder India 14 821 1.7× 208 1.0× 36 0.3× 63 0.7× 69 0.8× 68 905
Tommaso Caselli Netherlands 11 630 1.3× 77 0.4× 58 0.5× 28 0.3× 34 0.4× 75 690
Sheng-yi Kong Taiwan 7 721 1.5× 149 0.7× 40 0.3× 37 0.4× 70 0.8× 12 902
Andréi Popescu-Belis Switzerland 19 996 2.1× 216 1.0× 34 0.3× 31 0.3× 58 0.7× 116 1.2k
Chikashi Nobata Japan 16 1.4k 3.0× 351 1.6× 429 3.5× 121 1.3× 156 1.8× 40 1.6k
Daisuke Kawahara Japan 19 1.3k 2.8× 193 0.9× 78 0.6× 34 0.4× 23 0.3× 139 1.5k
Samhaa R. El-Beltagy Egypt 15 992 2.1× 339 1.6× 40 0.3× 29 0.3× 31 0.4× 63 1.1k
Francesca Spezzano United States 14 419 0.9× 179 0.8× 30 0.2× 43 0.5× 78 0.9× 63 733
Laurent Romary France 17 945 2.0× 191 0.9× 94 0.8× 13 0.1× 36 0.4× 134 1.2k
Dmitry Davidov Israel 11 1.1k 2.4× 261 1.2× 29 0.2× 73 0.8× 21 0.2× 18 1.3k

Countries citing papers authored by Dolf Trieschnigg

Since Specialization
Citations

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

Fields of papers citing papers by Dolf Trieschnigg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dolf Trieschnigg

This figure shows the co-authorship network connecting the top 25 collaborators of Dolf Trieschnigg. A scholar is included among the top collaborators of Dolf Trieschnigg 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 Dolf Trieschnigg. Dolf Trieschnigg 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.
Theune, Mariët, et al.. (2018). Supporting the Exploration of Online Cultural Heritage Collections: The Case of the Dutch Folktale Database. Digital humanities quarterly. 11(4). 4 indexed citations
2.
Demeester, Thomas, Dolf Trieschnigg, Dong Nguyen, Djoerd Hiemstra, & Ke Zhou. (2015). FedWeb Greatest Hits. University of Twente Research Information. 27–28. 8 indexed citations
3.
Nguyen, Dong, Dolf Trieschnigg, A. Seza Doğruöz, et al.. (2014). Why Gender and Age Prediction from Tweets is Hard: Lessons from a Crowdsourcing Experiment. University of Twente Research Information. 1950–1961. 61 indexed citations
4.
Demeester, Thomas, Dolf Trieschnigg, Dong Nguyen, & Djoerd Hiemstra. (2014). Overview of the TREC 2013 Federated Web Search Track. Ghent University Academic Bibliography (Ghent University). 1–11. 25 indexed citations
5.
Nguyen, Dong, Dolf Trieschnigg, A. Seza Doğruöz, et al.. (2014). COLING 2014, 25th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, August 23-29, 2014, Dublin, Ireland. 15 indexed citations
6.
Nguyen, Dong, Dolf Trieschnigg, & Mariët Theune. (2014). Using Crowdsourcing to Investigate Perception of Narrative Similarity. University of Twente Research Information. 321–330. 9 indexed citations
7.
Demeester, Thomas, Robin Aly, Djoerd Hiemstra, et al.. (2014). Exploiting user disagreement for web search evaluation. University of Twente Research Information. 33–42. 8 indexed citations
8.
Aly, Robin, Djoerd Hiemstra, Dolf Trieschnigg, & Thomas Demeester. (2013). Mirex and Taily at TREC 2013. Ghent University Academic Bibliography (Ghent University). 1–6. 1 indexed citations
9.
Nguyen, Dong, et al.. (2013). Proceedings of the Seventh International Conference on Weblogs and Social Media, ICWSM 2013, Cambridge, Massachusetts, USA, July 8-11, 2013.. National Conference on Artificial Intelligence. 8 indexed citations
10.
Trieschnigg, Dolf, Dong Nguyen, & Mariët Theune. (2013). Learning to Extract Folktale Keywords. Edinburgh Research Explorer (University of Edinburgh). 65–73.
11.
Nguyen, Dong, et al.. (2012). Federated Search in the Wild. KNAW research portal (Royal Academy of Art and Sciences (KNAW)). 1 indexed citations
12.
Trieschnigg, Dolf, et al.. (2012). Ranking XPaths for extracting search result records. CTIT technical report series. 8 indexed citations
13.
Hiemstra, Djoerd, et al.. (2012). Peer-to-Peer Information Retrieval. ACM Transactions on Information Systems. 30(2). 1–34. 13 indexed citations
14.
Nguyen, Dong, Thomas Demeester, Dolf Trieschnigg, & Djoerd Hiemstra. (2012). Federated search in the wild. University of Twente Research Information. 1874–1878. 27 indexed citations
15.
Nguyen, Dong, Dolf Trieschnigg, T. Meder, & Mariët Theune. (2012). Automatic classification of folk narrative genres. University of Twente Research Information. 378–382. 7 indexed citations
16.
Meij, Edgar, Dolf Trieschnigg, Maarten de Rijke, & Wessel Kraaij. (2009). Conceptual language models for domain-specific retrieval. Information Processing & Management. 46(4). 448–469. 31 indexed citations
17.
Trieschnigg, Dolf, et al.. (2009). MeSH Up: effective MeSH text classification for improved document retrieval. Bioinformatics. 25(11). 1412–1418. 67 indexed citations
18.
Schuemie, Martijn J., Dolf Trieschnigg, & Wessel Kraaij. (2007). Cross Language Information Retrieval for Biomedical Literature. TNO Repository. 4 indexed citations
19.
Trieschnigg, Dolf, Wessel Kraaij, & Martijn J. Schuemie. (2006). Concept based document retrieval for genomics literature. TNO Repository. 11 indexed citations
20.
Trieschnigg, Dolf & Wessel Kraaij. (2005). Hierarchical Topic Detection in Large Digital News Archives: Exploring a Sample Based Approach. Journal of Digital Information Management. 3(1). 21–27. 5 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.

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