What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Algorithm
- Machine learning
Raymond Chi-Wing Wong mainly focuses on Data mining, Theoretical computer science, Data publishing, Computer security and Artificial intelligence.
Many of his research projects under Data mining are closely connected to Sliding window protocol and Ask price with Sliding window protocol and Ask price, tying the diverse disciplines of science together.
The study incorporates disciplines such as Scalability, Spatial database, k-nearest neighbors algorithm, Algorithm and Point in addition to Theoretical computer science.
Raymond Chi-Wing Wong has researched Data publishing in several fields, including Adversary and k-anonymity.
His k-anonymity study combines topics from a wide range of disciplines, such as Data anonymization, Information sensitivity and Identification.
His work investigates the relationship between Artificial intelligence and topics such as Machine learning that intersect with problems in Quadratic programming.
His most cited work include:
- (α, k)-anonymity: an enhanced k-anonymity model for privacy preserving data publishing (531 citations)
- Minimality attack in privacy preserving data publishing (258 citations)
- Efficient method for maximizing bichromatic reverse nearest neighbor (103 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Data mining, Theoretical computer science, Artificial intelligence, Algorithm and Data publishing.
His research in the fields of Skyline overlaps with other disciplines such as Order.
Raymond Chi-Wing Wong combines subjects such as Orders of magnitude, k-nearest neighbors algorithm, Graph, Function and Computation with his study of Theoretical computer science.
The various areas that Raymond Chi-Wing Wong examines in his Artificial intelligence study include Machine learning and Pattern recognition.
His work deals with themes such as Adversary, Information sensitivity and Information privacy, k-anonymity, which intersect with Data publishing.
His Information sensitivity research incorporates themes from Internet privacy and Anonymity.
He most often published in these fields:
- Data mining (25.61%)
- Theoretical computer science (18.90%)
- Artificial intelligence (10.37%)
What were the highlights of his more recent work (between 2019-2021)?
- Theoretical computer science (18.90%)
- Information retrieval (6.71%)
- Tuple (6.10%)
In recent papers he was focusing on the following fields of study:
Raymond Chi-Wing Wong mostly deals with Theoretical computer science, Information retrieval, Tuple, Data mining and Regret.
His research integrates issues of Location intelligence, Server and K nearest neighbour in his study of Theoretical computer science.
His study in Information retrieval is interdisciplinary in nature, drawing from both Range and Language model, Speech recognition.
The Tuple study combines topics in areas such as Dynamic problem, Orders of magnitude, Function, Ranking and Skyline.
Raymond Chi-Wing Wong works mostly in the field of Data mining, limiting it down to concerns involving Location-based service and, occasionally, Piecewise constant approximation and Approximation algorithm.
Raymond Chi-Wing Wong has included themes like Bridging and Mathematical optimization in his Regret study.
Between 2019 and 2021, his most popular works were:
- Handling Information Loss of Graph Neural Networks for Session-based Recommendation (10 citations)
- An experimental survey of regret minimization query and variants: bridging the best worlds between top- k query and skyline query (8 citations)
- When Do GNNs Work: Understanding and Improving Neighborhood Aggregation (6 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Algorithm
- Machine learning
Raymond Chi-Wing Wong spends much of his time researching Tuple, Graph, Theoretical computer science, Data science and Graph neural networks.
His Tuple research is multidisciplinary, incorporating perspectives in Bridging, Regret minimization, Regret, Information retrieval and Skyline.
His Graph research incorporates elements of Algorithm and Recommender system.
His studies in Theoretical computer science integrate themes in fields like Function, Perspective and Real number.
He undertakes multidisciplinary investigations into Data science and Work in his work.
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