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.
An empirical comparison of botnet detection methods
Countries citing papers authored by Alejandro Zunino
Since
Specialization
Citations
This map shows the geographic impact of Alejandro Zunino'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 Alejandro Zunino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alejandro Zunino more than expected).
Fields of papers citing papers by Alejandro Zunino
This network shows the impact of papers produced by Alejandro Zunino. 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 Alejandro Zunino. The network helps show where Alejandro Zunino may publish in the future.
Co-authorship network of co-authors of Alejandro Zunino
This figure shows the co-authorship network connecting the top 25 collaborators of Alejandro Zunino.
A scholar is included among the top collaborators of Alejandro Zunino 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 Alejandro Zunino. Alejandro Zunino is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Mateos, Cristian, et al.. (2015). Assisting developers to build high-quality code-first web service APIs. Journal of Web Engineering. 14(3). 251–285.7 indexed citations
10.
Garriga, Martín, et al.. (2015). Adaptability-based Service Behavioral Assessment. SHILAP Revista de lepidopterología.1 indexed citations
11.
Salinas, Sergio, Carlos García Garino, & Alejandro Zunino. (2014). PFS: A Productivity Forecasting System for Desktop Computers to Improve Grid Applications Performance in Enterprise Desktop Grid. Americanae (AECID Library). 33(4). 783–809.1 indexed citations
12.
Rodríguez, Juan Manuel, et al.. (2014). Usage pattern mining for smartphone use personalization. Human Factors in Computing Systems. 377–380.1 indexed citations
Crasso, Marco, et al.. (2012). Estimating Web Service interface complexity and quality through conventional object-oriented metrics.. Conferencia Iberoamericana de Software Engineering. 154–167.4 indexed citations
16.
Garriga, Martín, et al.. (2012). Practical Assessment Scheme to Service Selection for SOC-based Applications. Americanae (AECID Library).2 indexed citations
17.
Mateos, Cristian, et al.. (2011). A NOVEL MECHANISM FOR GRIDIFICATION OF COMPILED JAVA APPLICATIONS. Computing and Informatics / Computers and Artificial Intelligence. 30(6). 1259–1285.4 indexed citations
Crasso, Marco, et al.. (2010). Empirically assessing the impact of dependency injection on the development of web service applications. Journal of Web Engineering. 9(1). 66–94.5 indexed citations
20.
Zunino, Alejandro. (2002). Brainstorm/J: Un framework para agentes inteligentes. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).1 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.