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 Calton Pu'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 Calton Pu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Calton Pu more than expected).
This network shows the impact of papers produced by Calton Pu. 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 Calton Pu. The network helps show where Calton Pu may publish in the future.
Co-authorship network of co-authors of Calton Pu
This figure shows the co-authorship network connecting the top 25 collaborators of Calton Pu.
A scholar is included among the top collaborators of Calton Pu 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 Calton Pu. Calton Pu is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Webb, Steve, James Caverlee, & Calton Pu. (2008). Social Honeypots: Making Friends With A Spammer Near You..77 indexed citations
3.
Lee, Chin‐Hui, et al.. (2007). A Discriminative Classifier Learning Approach to Image Modeling and Spam Image Identification.22 indexed citations
4.
Koh, Younggyun, Calton Pu, Sapan Bhatia, & Charles Consel. (2006). Efficient Packet Processing in User-Level Operating Systems: A Study of UML. HAL (Le Centre pour la Communication Scientifique Directe).1 indexed citations
5.
Webb, Steve, James Caverlee, & Calton Pu. (2006). Introducing the Webb Spam Corpus: Using Email Spam to Identify Web Spam Automatically.66 indexed citations
6.
Pu, Calton & Steve Webb. (2006). Observed Trends in Spam Construction Techniques: A Case Study of Spam Evolution..50 indexed citations
Fileto, Renato, Cláudia Bauzer Medeiros, Ling Liu, Calton Pu, & Eduardo Delgado Assad. (2003). Using Domain Ontologies to Help Track Data Provenance.. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 41(6). 84–98.6 indexed citations
10.
Walpole, Jonathan, et al.. (2001). A Rate-Matching Packet Scheduler for Real-Rate Applications. PDXScholar (Portland State University).3 indexed citations
Liu, Ling & Calton Pu. (1996). Issues on Query Processing in Distributed and Interoperable Information Systems.. 70–79.1 indexed citations
13.
O׳Neil, Patrick E., Krithi Ramamritham, & Calton Pu. (1995). A two-phase approach to predictably scheduling real-time transactions. Prentice-Hall, Inc eBooks. 494–522.14 indexed citations
14.
Pu, Calton, et al.. (1993). ACID Properties Need Fast Relief: Relaxing Consistency Using Epsilon Serializability.. 0.3 indexed citations
15.
Kaiser, Gail E. & Calton Pu. (1992). Dynamic restructuring of transactions. Morgan Kaufmann Publishers Inc. eBooks. 45(1). 265–295.18 indexed citations
Elmagarmid, Ahmed K. & Calton Pu. (1990). Guest Editors' Introduction to the Special Issue on Heterogeneous Databases.. ACM Computing Surveys. 22. 175–178.24 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.