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.
Research-paper recommender systems: a literature survey
2015460 citationsJoeran Beel, Béla Gipp 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 Joeran Beel'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 Joeran Beel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Joeran Beel more than expected).
This network shows the impact of papers produced by Joeran Beel. 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 Joeran Beel. The network helps show where Joeran Beel may publish in the future.
Co-authorship network of co-authors of Joeran Beel
This figure shows the co-authorship network connecting the top 25 collaborators of Joeran Beel.
A scholar is included among the top collaborators of Joeran Beel 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 Joeran Beel. Joeran Beel 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.
Beel, Joeran, et al.. (2021). Time-dependent Evaluation of Recommender Systems.. Conference on Recommender Systems.1 indexed citations
2.
Sansonetti, Giuseppe, et al.. (2019). BERT, ELMo, use and infersent sentence encoders: The Panacea for research-paper recommendation?. Conference on Recommender Systems. 2431. 6–10.22 indexed citations
3.
Beel, Joeran, et al.. (2019). Data Pruning in Recommender Systems Research: Best-Practice or Malpractice?. Conference on Recommender Systems. 26–30.1 indexed citations
4.
Beel, Joeran, et al.. (2019). A First Analysis of Meta-Learned Per-Instance Algorithm Selection in Scholarly Recommender Systems.. Conference on Recommender Systems. 29–34.2 indexed citations
5.
Beel, Joeran, et al.. (2019). GIANT: The 1-Billion Annotated Synthetic Bibliographic-Reference-String Dataset for Deep Citation Parsing.. 260–271.1 indexed citations
Beel, Joeran, Corinna Breitinger, Stefan Langer, Andreas Lommatzsch, & Béla Gipp. (2016). Towards reproducibility in recommender-systems research. User Modeling and User-Adapted Interaction. 26(1). 69–101.36 indexed citations
12.
Beel, Joeran, Marcel Genzmehr, & Stefan Langer. (2013). Docear4Word. 445–446.
Gipp, Béla & Joeran Beel. (2009). Identifying Related Documents For Research Paper Recommender By CPA And COA. World Congress on Engineering. 636–639.12 indexed citations
17.
Gipp, Béla, Joeran Beel, & Christian Hentschel. (2009). Scienstein : A Research Paper Recommender System. 309–315.62 indexed citations
18.
Gipp, Béla & Joeran Beel. (2009). Citation Proximity Analysis (CPA) : A New Approach for Identifying Related Work Based on Co-Citation Analysis. KOPS (University of Konstanz). 571–575.85 indexed citations
19.
Gipp, Béla, et al.. (2007). ePassport: The World's New Electronic Passport: A Report about the ePassport's Benefits, Risks and its Security.3 indexed citations
20.
Beel, Joeran, et al.. (2004). UbiLoc : A System for Locating Mobile Devices using Mobile Devices. 43–48.5 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.