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.
Optimal aggregation algorithms for middleware
2001688 citationsRonald Fagin, Amnon Lotem et al.profile →
Optimal aggregation algorithms for middleware
2003592 citationsRonald Fagin, Amnon Lotem et al.Journal of Computer and System Sciencesprofile →
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 Amnon Lotem'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 Amnon Lotem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amnon Lotem more than expected).
This network shows the impact of papers produced by Amnon Lotem. 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 Amnon Lotem. The network helps show where Amnon Lotem may publish in the future.
Co-authorship network of co-authors of Amnon Lotem
This figure shows the co-authorship network connecting the top 25 collaborators of Amnon Lotem.
A scholar is included among the top collaborators of Amnon Lotem 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 Amnon Lotem. Amnon Lotem is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
11 of 11 papers shown
1.
Fagin, Ronald, Amnon Lotem, & Moni Naor. (2003). Optimal aggregation algorithms for middleware. Journal of Computer and System Sciences. 66(4). 614–656.592 indexed citations breakdown →
2.
Nau, Dana, Yue Cao, Amnon Lotem, & Héctor Muñoz‐Avila. (2001). The Shop Planning System. AI Magazine. 22(3). 91.16 indexed citations
3.
Fagin, Ronald, Amnon Lotem, & Moni Naor. (2001). Optimal aggregation algorithms for middleware. 102–113.688 indexed citations breakdown →
4.
Nau, Dana, et al.. (2001). Total-order planning with partially ordered subtasks. 425–430.64 indexed citations
5.
Lotem, Amnon & Dana Nau. (2000). New advances in GraphHTN: identifying independent subproblems in large HTN domains. 206–215.7 indexed citations
6.
Vossen, Thomas, Michael O. Ball, Amnon Lotem, & Dana Nau. (2000). Applying integer programming to AI planning. The Knowledge Engineering Review. 15(1). 85–100.16 indexed citations
Lotem, Amnon, Dana Nau, & James Hendler. (1999). Using planning graphs for solving HTN planning problems. National Conference on Artificial Intelligence. 534–540.12 indexed citations
9.
Vossen, Thomas, Michael O. Ball, Amnon Lotem, & Dana Nau. (1999). On the use of integer programming models in AI planning. Digital Repository at the University of Maryland (University of Maryland College Park). 304–309.66 indexed citations
10.
Nau, Dana, Yue Cao, Amnon Lotem, & Héctor Muñoz‐Avila. (1999). SHOP: Simple Hierarchical Ordered Planner. Digital Repository at the University of Maryland (University of Maryland College Park). 968–975.225 indexed citations
11.
Vossen, Thomas, Michael O. Ball, Amnon Lotem, & Dana Nau. (1998). Integer Programming Models in AI Planning: Preliminary Experimental Results.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.