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.
Sequence classification for credit-card fraud detection
2018268 citationsMichael Granitzer et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Michael Granitzer
Since
Specialization
Citations
This map shows the geographic impact of Michael Granitzer'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 Michael Granitzer with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Granitzer more than expected).
Fields of papers citing papers by Michael Granitzer
This network shows the impact of papers produced by Michael Granitzer. 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 Michael Granitzer. The network helps show where Michael Granitzer may publish in the future.
Co-authorship network of co-authors of Michael Granitzer
This figure shows the co-authorship network connecting the top 25 collaborators of Michael Granitzer.
A scholar is included among the top collaborators of Michael Granitzer 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 Michael Granitzer. Michael Granitzer is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Caselli, Tommaso, et al.. (2020). I Feel Offended, Don’t Be Abusive!: Implicit/Explicit Messages in Offensive and Abusive Language. Language Resources and Evaluation. 6193–6202.56 indexed citations
4.
Mitrović, Jelena, et al.. (2020). Language Proficiency Scoring. Language Resources and Evaluation. 5624–5630.3 indexed citations
Granitzer, Michael, et al.. (2013). Unfolding Cultural, Educational and Scientific Long-Tail Content in the Web. University of Twente Research Information.4 indexed citations
7.
Granitzer, Michael, et al.. (2013). Towards disambiguating web tables. University of Twente Research Information. 205–208.10 indexed citations
8.
Shahzad, Syed Khuram, Michael Granitzer, & Denis Helić. (2012). Ontological model driven GUI development: User Interface Ontology approach. 214–218.5 indexed citations
9.
Granitzer, Michael & Stefanie Lindstaedt. (2011). Semantic Web: Theory and Applicationsns.. JUCS - Journal of Universal Computer Science. 17. 981–982.1 indexed citations
10.
Lindstaedt, Stefanie & Michael Granitzer. (2011). Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies.14 indexed citations
Kern, Roman, et al.. (2010). KCDC: Word Sense Induction by Using Grammatical Dependencies and Sentence Phrase Structure. Meeting of the Association for Computational Linguistics. 351–354.9 indexed citations
13.
Granitzer, Michael, et al.. (2009). Distributed Web 2.0 Crawling for Ontology Evolution. Journal of Digital Information Management. 7(2). 114–119.3 indexed citations
14.
Lex, Elisabeth, et al.. (2009). Facet Classification of Blogs: Know-Center at the TREC 2009 Blog Distillation Task. Text REtrieval Conference. 0–0.
15.
Lex, Elisabeth, et al.. (2009). Automated Blog Classification: A Cross Domain Approach. Data Archiving and Networked Services (DANS). 598–605.
16.
Sabol, Vedran, et al.. (2009). Knowledge Discovery using the Knowminer Framework. International Conference on Information Systems. 307–314.8 indexed citations
17.
Lex, Elisabeth, Christin Seifert, Wolfgang Kienreich, & Michael Granitzer. (2008). A Generic Framework for Visualizing the News Article Domain and its Application to Real-World Data. Journal of Digital Information Management. 6(6). 434–441.5 indexed citations
18.
Sabol, Vedran, et al.. (2007). Visualization Metaphors for Multi-modal Meeting Data.. 250–269.3 indexed citations
19.
Kröll, Mark, et al.. (2007). Task Instance Classification via Graph Kernels. 1–4.2 indexed citations
20.
Kappe, Frank, Wolfgang Kienreich, Vedran Sabol, et al.. (2003). InfoSky: Visual Exploration of Large Hierarchical Document Repositories. International Conference on Human-Computer Interaction. 1268–1272.4 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.