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.
This map shows the geographic impact of Dan Pelleg'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 Dan Pelleg with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Pelleg more than expected).
This network shows the impact of papers produced by Dan Pelleg. 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 Dan Pelleg. The network helps show where Dan Pelleg may publish in the future.
Co-authorship network of co-authors of Dan Pelleg
This figure shows the co-authorship network connecting the top 25 collaborators of Dan Pelleg.
A scholar is included among the top collaborators of Dan Pelleg 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 Dan Pelleg. Dan Pelleg is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Pelleg, Dan, et al.. (2017). Fun Facts. 345–354.13 indexed citations
3.
Ben‐Sasson, Ayelet, Dan Pelleg, & Elad Yom‐Tov. (2016). The quality of online answers to parents who suspect that their child has an Autism Spectrum Disorder. National Conference on Artificial Intelligence.
4.
Agichtein, Eugene, David Carmel, Dan Pelleg, Yuval Pinter, & Donna Harman. (2015). Overview of the TREC 2015 LiveQA Track.. Text REtrieval Conference.22 indexed citations
5.
Szpektor, Idan, Yoelle Maarek, & Dan Pelleg. (2013). When relevance is not enough. 1249–1260.43 indexed citations
Yom‐Tov, Elad, et al.. (2005). Juru at TREC 2005: Query Prediction in the Terabyte and the Robust tracks. Text REtrieval Conference.4 indexed citations
12.
Pelleg, Dan & Andrew Moore. (2004). Active Learning for Anomaly and Rare-Category Detection. Neural Information Processing Systems. 17. 1073–1080.92 indexed citations
13.
Pelleg, Dan & Andrew Moore. (2004). Scalable and practical probability density estimators for scientific anomaly detection.9 indexed citations
14.
Pelleg, Dan & Andrew Moore. (2002). Using Tarjan's Red Rule for Fast Dependency Tree Construction. Neural Information Processing Systems. 15. 825–833.7 indexed citations
15.
Pelleg, Dan & Andrew Moore. (2001). Mixtures of Rectangles: Interpretable Soft Clustering. International Conference on Machine Learning. 401–408.16 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.