H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 38 Citations 5,346 247 World Ranking 5137 National Ranking 225

Research.com Recognitions

Awards & Achievements

2017 - ACM Senior Member

Overview

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)

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

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)

289 Citations

DSTree: A Tree Structure for the Mining of Frequent Sets from Data Streams

C.K.-S. Leung;Q.I. Khan.
international conference on data mining (2006)

221 Citations

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)

191 Citations

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)

151 Citations

Efficient Mining of Frequent Patterns from Uncertain Data

C.K.-S. Leung;C.L. Carmichael;Boyu Hao.
international conference on data mining (2007)

149 Citations

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)

148 Citations

Mining of Frequent Itemsets from Streams of Uncertain Data

Carson Kai-Sang Leung;Boyu Hao.
international conference on data engineering (2009)

130 Citations

Efficient dynamic mining of constrained frequent sets

Laks V. S. Lakshmanan;Carson Kai-Sang Leung;Raymond T. Ng.
ACM Transactions on Database Systems (2003)

96 Citations

Sports Data Mining: Predicting Results for the College Football Games

Carson Kai-Sang Leung;Kyle W. Joseph.
Procedia Computer Science (2014)

87 Citations

Exploiting succinct constraints using FP-trees

Carson Kai-Sang Leung;Laks V. S. Lakshmanan;Raymond T. Ng.
Sigkdd Explorations (2002)

85 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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