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.
Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey
2019516 citationsGiang Nguyen, Štefan Dlugolinský et al.Artificial Intelligence Reviewprofile →
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 Viet Tran'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 Viet Tran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Viet Tran more than expected).
This network shows the impact of papers produced by Viet Tran. 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 Viet Tran. The network helps show where Viet Tran may publish in the future.
Co-authorship network of co-authors of Viet Tran
This figure shows the co-authorship network connecting the top 25 collaborators of Viet Tran.
A scholar is included among the top collaborators of Viet Tran 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 Viet Tran. Viet Tran is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Nguyen, Giang, et al.. (2016). Integrated System for Hydraulic Simulations. Computing and Informatics / Computers and Artificial Intelligence. 34(5). 1065–1088.4 indexed citations
10.
Hluchý, Ladislav, et al.. (2016). Effective Computation Resilience in High Performance and Distributed Environments. Computing and Informatics / Computers and Artificial Intelligence. 35(6). 1386–1415.8 indexed citations
11.
Bobák, Martin, Ladislav Hluchý, & Viet Tran. (2016). Application Performance Optimization in Multicloud Environment. Computing and Informatics / Computers and Artificial Intelligence. 35(6). 1359–1385.
12.
Nguyen, Binh Minh, Viet Tran, & Ladislav Hluchý. (2013). A Generic Development and Deployment Framework for Cloud Computing and Distributed Applications. Computing and Informatics / Computers and Artificial Intelligence. 32(3). 461–485.10 indexed citations
13.
Nguyen, Binh Minh, Viet Tran, & Ladislav Hluchý. (2012). Developing and Deploying Cloud Services Based on Abstraction Approach. Journal of Digital Information Management. 10(4). 254–261.1 indexed citations
14.
Nguyen, Binh Minh, Viet Tran, & Ladislav Hluchý. (2012). A high-level abstraction layer for cloud computing. 446–449.1 indexed citations
Hluchý, Ladislav, et al.. (2001). The mapping, scheduling and load balancing tools of GRADE. Nova Science Publishers, Inc. eBooks. 265–278.2 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.