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.
Latent dirichlet allocation for tag recommendation
2009326 citationsRalf Krestel, Péter Fankhauser et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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This map shows the geographic impact of Ralf Krestel'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 Ralf Krestel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ralf Krestel more than expected).
This network shows the impact of papers produced by Ralf Krestel. 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 Ralf Krestel. The network helps show where Ralf Krestel may publish in the future.
Co-authorship network of co-authors of Ralf Krestel
This figure shows the co-authorship network connecting the top 25 collaborators of Ralf Krestel.
A scholar is included among the top collaborators of Ralf Krestel 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 Ralf Krestel. Ralf Krestel is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Risch, Julian, et al.. (2021). ComEx: Comment Exploration on Online News Platforms..1 indexed citations
7.
Risch, Julian, Anke Stoll, Marc Ziegele, & Ralf Krestel. (2019). hpiDEDIS at GermEval 2019: Offensive Language Identification using a German BERT model..14 indexed citations
8.
Risch, Julian & Ralf Krestel. (2018). Aggression Identification Using Deep Learning and Data Augmentation. International Conference on Computational Linguistics. 150–158.30 indexed citations
9.
Krestel, Ralf, et al.. (2018). Topic-aware Network Visualisation to Explore Large Email Corpora.. EDBT/ICDT Workshops. 104–107.4 indexed citations
10.
Krestel, Ralf, et al.. (2017). Uncovering Business Relationships: Context-sensitive Relationship Extraction for Difficult Relationship Types.. 271.4 indexed citations
11.
Park, Jihyun, Margaret E. Blume‐Kohout, Ralf Krestel, Eric Nalisnick, & Padhraic Smyth. (2016). Analyzing NIH Funding Patterns over Time with Statistical Text Analysis.. National Conference on Artificial Intelligence.2 indexed citations
12.
Krestel, Ralf, et al.. (2016). Classification of German Newspaper Comments.. 299–310.
13.
Krestel, Ralf, et al.. (2016). Identifying Political Bias in News Articles.. 12.18 indexed citations
14.
Krestel, Ralf, et al.. (2015). How to Stay Up-To-Date on Twitter With General Keywords.. LWA. 373–381.1 indexed citations
Krestel, Ralf & Péter Fankhauser. (2009). Tag recommendation using probabilistic topic models. 131–141.26 indexed citations
17.
Krestel, Ralf, Sabine Bergler, & René Witte. (2008). Minding the Source: Automatic Tagging of Reported Speech in Newspaper Articles. Language Resources and Evaluation.32 indexed citations
18.
Witte, René, et al.. (2008). A Semantic Wiki Approach to Cultural Heritage Data Management.8 indexed citations
19.
Krestel, Ralf, Peter C. Lockemann, & René Witte. (2007). Automatic Analysis and Reasoning on Reported Speech in Newspaper Articles.5 indexed citations
20.
Krestel, Ralf, René Witte, & Sabine Bergler. (2007). Fuzzy set theory-based belief processing for natural language texts. National Conference on Artificial Intelligence. 1878–1879.1 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.