Wee Keong Ng mainly focuses on Data mining, Computer security, Data stream mining, Information retrieval and World Wide Web. Wee Keong Ng is involved in the study of Data mining that focuses on Association rule learning in particular. The Data stream mining study combines topics in areas such as Data stream clustering, Concept mining, Feature selection and Cluster analysis.
Wee Keong Ng combines subjects such as cXML, XML validation, Web page, Efficient XML Interchange and Simple API for XML with his study of Information retrieval. His study in World Wide Web focuses on Web navigation, Web standards, Web mapping, Web intelligence and Web 2.0. His Data Web research is multidisciplinary, incorporating perspectives in Static web page and Web query classification.
His main research concerns Data mining, World Wide Web, Web page, Database and Data Web. His Data mining study integrates concerns from other disciplines, such as Scalability and Cluster analysis, Artificial intelligence. His World Wide Web study incorporates themes from Data modeling and Information retrieval.
His research investigates the connection between Database and topics such as Encryption that intersect with problems in Server, Theoretical computer science and Protocol. The study incorporates disciplines such as Static web page, Web development, Web navigation and Web modeling in addition to Data Web. The Web development study which covers Web 2.0 that intersects with Web application security.
Encryption, Scalability, Computer security, Database and Information privacy are his primary areas of study. His Encryption research includes elements of Theoretical computer science, Cryptography, Outsourcing, Protocol and Server. His studies deal with areas such as Data mining, Database transaction, Blockchain, Smart contract and Artificial intelligence as well as Scalability.
His Data mining study combines topics in areas such as Wireless sensor network, Decision boundary, Support vector machine, Hyperplane and Optimization problem. In general Artificial intelligence, his work in Adaptive learning algorithm and Cluster analysis is often linked to Online learning linking many areas of study. His research in the fields of Relational database, Distributed data store and Database server overlaps with other disciplines such as Computer data storage.
His scientific interests lie mostly in Encryption, Scalability, Computer security, Database and Data mining. His Encryption research incorporates themes from Outsourcing and Information sensitivity. His work carried out in the field of Scalability brings together such families of science as Distributed computing, Protocol, Information privacy, Server and Big data.
Wee Keong Ng has researched Server in several fields, including Association rule learning, Overhead and Public-key cryptography. His study in the field of Distributed data store also crosses realms of Computer data storage. His Data mining research is multidisciplinary, relying on both Wireless sensor network, Face, Cluster analysis, Data stream clustering and Focus.
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Research Issues in Web Data Mining
Sanjay Kumar Madria;Sourav S. Bhowmick;Wee Keong Ng;Ee-Peng Lim.
data warehousing and knowledge discovery (1999)
A survey of Web metrics
Devanshu Dhyani;Wee Keong Ng;Sourav S. Bhowmick.
ACM Computing Surveys (2002)
Web classification using support vector machine
Aixin Sun;Ee-Peng Lim;Wee-Keong Ng.
web information and data management (2002)
A survey on data stream clustering and classification
Hai-Long Nguyen;Yew-Kwong Woon;Wee-Keong Ng.
Knowledge and Information Systems (2015)
Private data deduplication protocols in cloud storage
Wee Keong Ng;Yonggang Wen;Huafei Zhu.
acm symposium on applied computing (2012)
Ontologies and electronic commerce
D. Fensel;D.L. McGuiness;E. Schulten;Wee Keong Ng.
IEEE Intelligent Systems (2001)
Density-based clustering of data streams at multiple resolutions
Li Wan;Wee Keong Ng;Xuan Hong Dang;Philip S. Yu.
ACM Transactions on Knowledge Discovery From Data (2009)
Rapid association rule mining
Amitabha Das;Wee-Keong Ng;Yew-Kwong Woon.
conference on information and knowledge management (2001)
Block-oriented compression techniques for large statistical databases
Wee-Keong Ng;C.V. Ravishankar.
IEEE Transactions on Knowledge and Data Engineering (1997)
G-Portal: a map-based digital library for distributed geospatial and georeferenced resources
Ee-Peng Lim;Dion Hoe-Lian Goh;Zehua Liu;Wee-Keong Ng.
acm/ieee joint conference on digital libraries (2002)
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