Samuel Broscheit

543 citations
16 papers · 239 · h-index 9

Impact in

Papers in

    • Topic Modeling 11
    • Natural Language Processing Techniques 10
    • Advanced Graph Neural Networks 3
    • Semantic Web and Ontologies 2
    • Speech and dialogue systems 2
    • Domain Adaptation and Few-Shot Learning 1
    • Biomedical Text Mining and Ontologies 2

Samuel Broscheit

15 papers receiving 220 citations

Peers

Samuel Broscheit
Comparison fields: 5 of 30
  • Artificial Intelligence 213
  • Management Science and Operations Research 36
  • Statistical and Nonlinear Physics 15
  • Computer Vision and Pattern Recognition 21
  • Information Systems 21
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Citations per year

Countries citing papers authored by Samuel Broscheit

Since Specialization
Citations

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

Fields of papers citing papers by Samuel Broscheit

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Samuel Broscheit, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Samuel Broscheit Line = papers co-authored together Samuel Broscheit links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings
202052
2 202049
3
BART: A Multilingual Anaphora Resolution System
201029
4 202017
5
A Multigraph Model for Coreference Resolution
201216
6 201914
7 202312
8 201010
9
Rapid Bootstrapping of Word Sense Disambiguation Resources for German
20109
10 20186
11 20226
12 20215
13
OpenIE for Slot Filling at TAC KBP 2017 - System Description.
20175
14 20195
15
SUMMA at TAC Knowledge Base Population Task 2017.
20173
16 20161

About Samuel Broscheit

Samuel Broscheit is a scholar working on Artificial Intelligence, Molecular Biology, Management Science and Operations Research, Communication and Information Systems, having authored 16 papers that have together received 239 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers), Advanced Graph Neural Networks (3 papers), Semantic Web and Ontologies (2 papers), Data Quality and Management (2 papers), Speech and dialogue systems (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Artificial Intelligence (213 citations), Management Science and Operations Research (36 citations), Statistical and Nonlinear Physics (15 citations), Computer Vision and Pattern Recognition (21 citations) and Information Systems (21 citations). Samuel Broscheit has collaborated with scholars based in Germany, Italy and United States. Frequent co-authors include Rainer Gemulla, Daniel Ruffinelli, Kiril Gashteovski, Simone Paolo Ponzetto, Massimo Poesio, Yannick Versley, Heiner Stuckenschmidt, Lorenza Romano, Roberto Zanoli and Yanjie Wang. Their work appears in journals such as Theory and applications of categories, Nature Machine Intelligence, Language Resources and Evaluation, MADOC (University of Mannheim) and MADOC (University of Mannheim).

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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