His primary areas of study are Data mining, Artificial intelligence, Machine learning, Intrusion detection system and Data stream mining. In his research, he undertakes multidisciplinary study on Data mining and Credit card fraud. Wei Fan has researched Artificial intelligence in several fields, including Weighting, Graph and Pattern recognition.
His Machine learning study frequently links to related topics such as Classifier. His work carried out in the field of Intrusion detection system brings together such families of science as Security policy, Anomaly detection and Computer network, Mobile computing. His research integrates issues of Data stream and Training set in his study of Data stream mining.
Wei Fan spends much of his time researching Artificial intelligence, Data mining, Machine learning, Pattern recognition and Information retrieval. His studies in Artificial intelligence integrate themes in fields like Graph, Computer vision and Natural language processing. The Data mining study combines topics in areas such as Scalability and Cluster analysis.
His studies in Semi-supervised learning, Decision tree, Unsupervised learning, Boosting and Transfer of learning are all subfields of Machine learning research. His research ties Feature and Pattern recognition together. Many of his studies on Data stream mining involve topics that are commonly interrelated, such as Data stream.
His primary areas of investigation include Artificial intelligence, Pattern recognition, Information retrieval, Natural language processing and Computer vision. As part of his studies on Artificial intelligence, Wei Fan frequently links adjacent subjects like Machine learning. His study explores the link between Machine learning and topics such as Reduction that cross with problems in Class.
His research in Pattern recognition intersects with topics in Convolution and Code. His studies examine the connections between Information retrieval and genetics, as well as such issues in Key, with regards to Annotation. His Natural language processing research integrates issues from Classifier and Graph.
Wei Fan mostly deals with Artificial intelligence, Information retrieval, Artificial neural network, Question answering and Pattern recognition. His work deals with themes such as Computer vision and Natural language processing, which intersect with Artificial intelligence. The concepts of his Information retrieval study are interwoven with issues in Ranking, Key and Knowledge base.
The various areas that he examines in his Artificial neural network study include Psoriasis, Utterance, Data mining and Medical record. His Question answering research includes themes of Transfer of learning, Closed captioning, Knowledge extraction and Federated learning. His Deep learning study improves the overall literature in Machine learning.
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Mining concept-drifting data streams using ensemble classifiers
Haixun Wang;Wei Fan;Philip S. Yu;Jiawei Han.
knowledge discovery and data mining (2003)
Distributed data mining in credit card fraud detection
P.K. Chan;W. Fan;A.L. Prodromidis;S.J. Stolfo.
IEEE Intelligent Systems & Their Applications (1999)
Mining big data: current status, and forecast to the future
Wei Fan;Albert Bifet.
Sigkdd Explorations (2013)
AdaCost: Misclassification Cost-Sensitive Boosting
Wei Fan;Salvatore J. Stolfo;Junxin Zhang;Philip K. Chan.
international conference on machine learning (1999)
Cost-based modeling for fraud and intrusion detection: results from the JAM project
S.J. Stolfo;Wei Fan;Wenke Lee;A. Prodromidis.
darpa information survivability conference and exposition (2000)
Method and system for using intelligent agents for financial transactions, services, accounting, and advice
Daniel Schutzer;William Hull Forster;Huanrui Hu;Wenke Lee.
Toward cost-sensitive modeling for intrusion detection and response
Wenke Lee;Wei Fan;Matthew Miller;Salvatore J. Stolfo.
Journal of Computer Security (2002)
ViST: a dynamic index method for querying XML data by tree structures
Haixun Wang;Sanghyun Park;Wei Fan;Philip S. Yu.
international conference on management of data (2003)
Real time data mining-based intrusion detection
Wenke Lee;S.J. Stolfo;P.K. Chan;E. Eskin.
darpa information survivability conference and exposition (2001)
Resolving conflicts in heterogeneous data by truth discovery and source reliability estimation
Qi Li;Yaliang Li;Jing Gao;Bo Zhao.
international conference on management of data (2014)
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