What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Topology
His main research concerns Citation, Data mining, Bibliometrics, Bioinformatics and Information retrieval.
His study in Citation is interdisciplinary in nature, drawing from both Probability and statistics, Big data, Scientometrics, Data science and Sociology of scientific knowledge.
His research is interdisciplinary, bridging the disciplines of Community structure and Data mining.
His work in the fields of Community structure, such as Clique percolation method, overlaps with other areas such as Girvan–Newman algorithm.
He interconnects Interpretation, Local algorithm and Identification in the investigation of issues within Clique percolation method.
The various areas that Filippo Radicchi examines in his Information retrieval study include Citation analysis, Transformation, Function and Field.
His most cited work include:
- Benchmark graphs for testing community detection algorithms (2023 citations)
- Defining and identifying communities in networks. (1808 citations)
- Finding Statistically Significant Communities in Networks (712 citations)
What are the main themes of his work throughout his whole career to date?
Filippo Radicchi focuses on Citation, Statistical physics, Statistics, Complex network and Theoretical computer science.
His Citation study combines topics in areas such as Bibliometrics, Field and Data science.
As a part of the same scientific family, Filippo Radicchi mostly works in the field of Statistics, focusing on Quality and, on occasion, Test.
While the research belongs to areas of Theoretical computer science, Filippo Radicchi spends his time largely on the problem of Cluster analysis, intersecting his research to questions surrounding Benchmark.
In his work, Data mining is strongly intertwined with Community structure, which is a subfield of Benchmark.
His biological study spans a wide range of topics, including Clique percolation method and Algorithm.
He most often published in these fields:
- Citation (28.68%)
- Statistical physics (16.91%)
- Statistics (19.12%)
What were the highlights of his more recent work (between 2017-2021)?
- Complex network (13.24%)
- Network topology (10.29%)
- Identification (10.29%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Complex network, Network topology, Identification, Topology and Theoretical computer science.
His Complex network research integrates issues from Space and Quadratic equation.
His Identification research is classified as research in Data mining.
In his research, Graph is intimately related to Closeness, which falls under the overarching field of Data mining.
The Topology study combines topics in areas such as Enhanced Data Rates for GSM Evolution, Multiplex and Observability.
His work in Theoretical computer science covers topics such as Embedding which are related to areas like Cluster analysis and Dimension.
Between 2017 and 2021, his most popular works were:
- Science of science (314 citations)
- Changing demographics of scientific careers: The rise of the temporary workforce (41 citations)
- Characterizing the Analogy Between Hyperbolic Embedding and Community Structure of Complex Networks. (24 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Topology
Filippo Radicchi focuses on Complex network, Maximization, Identification, Topology and Data mining.
His Robustness research extends to the thematically linked field of Complex network.
Filippo Radicchi combines subjects such as Basis, Measure and Complete information with his study of Maximization.
His Identification research is multidisciplinary, incorporating elements of Algorithm and Set.
His research integrates issues of Multiplex and Leverage in his study of Topology.
His work in Data mining addresses subjects such as Closeness, which are connected to disciplines such as Graph.
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