Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Countries citing papers authored by Thomas Demeester
Since
Specialization
Citations
This map shows the geographic impact of Thomas Demeester'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 Thomas Demeester with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Demeester more than expected).
Fields of papers citing papers by Thomas Demeester
This network shows the impact of papers produced by Thomas Demeester. 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 Thomas Demeester. The network helps show where Thomas Demeester may publish in the future.
Co-authorship network of co-authors of Thomas Demeester
This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Demeester.
A scholar is included among the top collaborators of Thomas Demeester 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 Thomas Demeester. Thomas Demeester is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Bekoulis, Giannis, Johannes Deleu, Thomas Demeester, & Chris Develder. (2018). Adversarial training for multi-context joint entity and relation extraction. Ghent University Academic Bibliography (Ghent University).122 indexed citations
9.
Demeester, Thomas, et al.. (2015). Ghent University-IBCN participation in the TAC KBP 2015 cold start slot filling task. Theory and applications of categories.1 indexed citations
10.
Demeester, Thomas, Robin Aly, Djoerd Hiemstra, Dong Nguyen, & Chris Develder. (2015). Radboud Repository (Radboud University).4 indexed citations
11.
Demeester, Thomas, et al.. (2014). Using active learning and semantic clustering for noise reduction in distant supervision. Ghent University Academic Bibliography (Ghent University). 1–6.8 indexed citations
12.
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
13.
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
14.
Nguyen, Dong, et al.. (2012). Federated Search in the Wild. KNAW research portal (Royal Academy of Art and Sciences (KNAW)).1 indexed citations
15.
Demeester, Thomas, et al.. (2012). UGent Participation in the TAC 2013 Entity-Linking Task. Theory and applications of categories. 1–12.
16.
Demeester, Thomas, et al.. (2012). UGent Participation in the Microblog Track 2012. Text REtrieval Conference. 1–5.4 indexed citations
Bitran, Jacob D., Richard K. Desser, Thomas Demeester, & Harvey M. Golomb. (1978). Metastatic non-oat-cell bronchogenic carcinoma. Therapy with cyclophosphamide, doxorubicin, methotrexate, and procarbazine (CAMP).. Munich Personal RePEc Archive (Ludwig Maximilian University of Munich). 240(25). 2743–6.29 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.