2017 - ACM Senior Member
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 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.
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.
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A tree-based approach for frequent pattern mining from uncertain data
Carson Kai-Sang Leung;Mark Anthony F. Mateo;Dale A. Brajczuk.
knowledge discovery and data mining (2008)
DSTree: A Tree Structure for the Mining of Frequent Sets from Data Streams
Carson Leung;Quamrul Khan.
international conference on data mining (2006)
CanTree: a canonical-order tree for incremental frequent-pattern mining
Carson Kai-Sang Leung;Quamrul I. Khan;Zhan Li;Tariqul Hoque.
Knowledge and Information Systems (2007)
Efficient Mining of Frequent Patterns from Uncertain Data
C.K.-S. Leung;C.L. Carmichael;Boyu Hao.
international conference on data mining (2007)
CanTree: a tree structure for efficient incremental mining of frequent patterns
C.K.-S. Leung;Q.I. Khan;T. Hoque.
international conference on data mining (2005)
Strength indices from pQCT imaging predict up to 85% of variance in bone failure properties at tibial epiphysis and diaphysis.
S A Kontulainen;J D Johnston;D Liu;C Leung.
Journal of Musculoskeletal & Neuronal Interactions (2008)
Mining of Frequent Itemsets from Streams of Uncertain Data
Carson Kai-Sang Leung;Boyu Hao.
international conference on data engineering (2009)
Sports Data Mining: Predicting Results for the College Football Games
Carson Kai-Sang Leung;Kyle W. Joseph.
Procedia Computer Science (2014)
Efficient dynamic mining of constrained frequent sets
Laks V. S. Lakshmanan;Carson Kai-Sang Leung;Raymond T. Ng.
ACM Transactions on Database Systems (2003)
Exploiting succinct constraints using FP-trees
Carson Kai-Sang Leung;Laks V. S. Lakshmanan;Raymond T. Ng.
Sigkdd Explorations (2002)
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