What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- The Internet
Jon Kleinberg mainly investigates Social network, World Wide Web, Theoretical computer science, Data science and Structure.
The concepts of his Social network study are interwoven with issues in Information cascade, Data mining and Artificial intelligence.
He has researched Artificial intelligence in several fields, including Simple and Dynamic network analysis.
As a member of one scientific family, Jon Kleinberg mostly works in the field of World Wide Web, focusing on Graph and, on occasion, Association rule learning, Connectivity and Directed graph.
While the research belongs to areas of Theoretical computer science, he spends his time largely on the problem of Range, intersecting his research to questions surrounding Phenomenon and Network model.
His Data science study integrates concerns from other disciplines, such as Scale, Presentation, Behavioral pattern, Interpersonal ties and Social media.
His most cited work include:
- Authoritative sources in a hyperlinked environment (7452 citations)
- Maximizing the spread of influence through a social network (4896 citations)
- The link-prediction problem for social networks (2915 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Social network, Theoretical computer science, Artificial intelligence, Algorithm and Data science.
His biological study spans a wide range of topics, including Data mining, Structure, Set, Social media and Dynamic network analysis.
The subject of his Social media research is within the realm of World Wide Web.
His studies in Theoretical computer science integrate themes in fields like Graph and Graph.
His work on Artificial intelligence is being expanded to include thematically relevant topics such as Machine learning.
His research on Algorithm frequently links to adjacent areas such as Discrete mathematics.
He most often published in these fields:
- Social network (14.57%)
- Theoretical computer science (12.11%)
- Artificial intelligence (10.99%)
What were the highlights of his more recent work (between 2015-2021)?
- Artificial intelligence (10.99%)
- Theoretical computer science (12.11%)
- Machine learning (6.50%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Theoretical computer science, Machine learning, Structure and Social media.
His research integrates issues of Hypergraph, Graph and Graph in his study of Theoretical computer science.
His Graph research integrates issues from Data mining and Pairwise comparison.
He works mostly in the field of Machine learning, limiting it down to concerns involving Medical imaging and, occasionally, Deep learning, Feature and Transfer of learning.
Jon Kleinberg has included themes like Completeness, Randomness and TRACE in his Structure study.
His Social media research includes themes of Information cascade and Social network.
Between 2015 and 2021, his most popular works were:
- Inherent Trade-Offs in the Fair Determination of Risk Scores (455 citations)
- On Fairness and Calibration (259 citations)
- Human Decisions and Machine Predictions (226 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- The Internet
Jon Kleinberg mainly focuses on Artificial intelligence, Machine learning, Social network, Social media and Algorithm.
His Artificial intelligence research incorporates elements of Recommender system and Scale.
His Machine learning study incorporates themes from Inference and Medical imaging.
His Social network research includes elements of Weighted network, Microeconomics, Interpersonal ties and Computer network, Dynamic network analysis.
His work deals with themes such as Cognitive psychology, Popularity and Information cascade, which intersect with Social media.
His Data mining research is multidisciplinary, relying on both Graph and Pairwise comparison.
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