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.
Some stylized facts of the Bitcoin market
2017346 citationsAurelio F. Bariviera, María José Basgall et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Waldo Hasperué
Since
Specialization
Citations
This map shows the geographic impact of Waldo Hasperué'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 Waldo Hasperué with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Waldo Hasperué more than expected).
This network shows the impact of papers produced by Waldo Hasperué. 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 Waldo Hasperué. The network helps show where Waldo Hasperué may publish in the future.
Co-authorship network of co-authors of Waldo Hasperué
This figure shows the co-authorship network connecting the top 25 collaborators of Waldo Hasperué.
A scholar is included among the top collaborators of Waldo Hasperué 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 Waldo Hasperué. Waldo Hasperué is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Hasperué, Waldo, et al.. (2021). Procesamiento inteligente de grandes volúmenes de información y de flujos de datos. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).1 indexed citations
Hasperué, Waldo, et al.. (2018). D3CAS: un algoritmo de clustering para el procesamiento de flujos de datos en spark. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).1 indexed citations
Lanzarini, Laura Cristina, et al.. (2015). Redes neuronales artificiales.
11.
Hasperué, Waldo, et al.. (2014). Keyword extracting using auto-associative neural networks. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).2 indexed citations
12.
Lanzarini, Laura Cristina, et al.. (2013). Caracterización de la deserción universitaria en la UNRN utilizando Minería de Datos. SHILAP Revista de lepidopterología.
13.
Lanzarini, Laura Cristina, et al.. (2013). Characterization of university drop-out at UNRN using data mining. A study case. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).1 indexed citations
14.
Hasperué, Waldo, et al.. (2013). A novel, Language-Independent Keyword Extraction method. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).4 indexed citations
15.
Lanzarini, Laura Cristina, et al.. (2013). Caracterización de la deserción universitaria en la UNRN utilizando Minería de Datos: Un caso de estudio. Americanae (AECID Library). 92–98.1 indexed citations
16.
Lanzarini, Laura Cristina, et al.. (2012). Técnicas de Optimización.
17.
Hasperué, Waldo, et al.. (2012). CLUIN – a new method for extracting rules for large databases. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).
18.
Lanzarini, Laura Cristina, et al.. (2010). Face recognition using SIFT and binary PSO descriptors. Information Technology Interfaces. 557–562.5 indexed citations
19.
Hasperué, Waldo, et al.. (2006). Skeletonization of sparse shapes using dynamic competitive neural networks. El Servicio de Difusión de la Creación Intelectual (National University of La Plata).
20.
Hasperué, Waldo & Laura Cristina Lanzarini. (2006). Classification rules obtained from dynamic self-organizing maps. 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.