What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Data mining
- Machine learning
His main research concerns Data mining, Uncertain data, Tree, Data stream mining and Database transaction.
His Data mining research incorporates themes from Tree structure and Wireless sensor network.
His studies in Uncertain data integrate themes in fields like Probabilistic logic, Key and Data mining algorithm.
Carson K. Leung is involved in the study of Tree that focuses on Tree based in particular.
His Data stream mining research is multidisciplinary, relying on both Sliding window protocol, Knowledge extraction and STREAMS.
In Big data, he works on issues like Data science, which are connected to Social network analysis, Data visualization and Representation.
His most cited work include:
- A tree-based approach for frequent pattern mining from uncertain data (191 citations)
- DSTree: A Tree Structure for the Mining of Frequent Sets from Data Streams (151 citations)
- CanTree: a canonical-order tree for incremental frequent-pattern mining (123 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Data mining, Big data, Data science, Uncertain data and Data stream mining.
The study incorporates disciplines such as Tree and Database transaction in addition to Data mining.
His research in Big data intersects with topics in Variety, Artificial intelligence, Machine learning and Data analysis.
His Data science research focuses on Social network and how it connects with Interdependence and Internet privacy.
Uncertain data is closely attributed to Probabilistic logic in his work.
The various areas that Carson K. Leung examines in his Data stream mining study include Sliding window protocol, Wireless sensor network and STREAMS.
He most often published in these fields:
- Data mining (39.47%)
- Big data (33.83%)
- Data science (27.07%)
What were the highlights of his more recent work (between 2019-2021)?
- Big data (33.83%)
- Data science (27.07%)
- Variety (9.02%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Big data, Data science, Variety, Analytics and Predictive analytics.
The Big data study combines topics in areas such as Data modeling, Machine learning and Knowledge extraction, Artificial intelligence.
His studies deal with areas such as Fuzzy control system, Fuzzy logic, Time series, Algorithm and Random forest as well as Knowledge extraction.
The concepts of his Data science study are interwoven with issues in Social network analysis, Open data and Focus.
His work deals with themes such as Visual analytics, Big data mining and Social network, which intersect with Variety.
Carson K. Leung has included themes like Internet privacy and Knowledge engineering in his Social network study.
Between 2019 and 2021, his most popular works were:
- Effective privacy preserving data publishing by vectorization (17 citations)
- An Innovative Big Data Predictive Analytics Framework over Hybrid Big Data Sources with an Application for Disease Analytics (10 citations)
- Big Data Analytics of Twitter Data and Its Application for Physician Assistants: Who Is Talking About Your Profession in Twitter? (7 citations)
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