Qing Li mainly investigates Information retrieval, Artificial intelligence, Data mining, World Wide Web and Database. Qing Li has included themes like Linear programming, Pattern recognition and Natural language processing in his Artificial intelligence study. The concepts of his Linear programming study are interwoven with issues in Contextual image classification, Entropy, Image quality and Image translation.
The Data mining study combines topics in areas such as Machine learning, Set and Trajectory. His World Wide Web study combines topics in areas such as Multimedia, Cluster analysis and Distance education. His work deals with themes such as Software engineering and k-nearest neighbors algorithm, which intersect with Database.
His scientific interests lie mostly in Artificial intelligence, Data mining, Information retrieval, World Wide Web and Database. His Artificial intelligence research is multidisciplinary, incorporating elements of Natural language processing, Task, Computer vision, Machine learning and Pattern recognition. His Data mining research incorporates themes from Object, Set and Cluster analysis.
He works on Information retrieval which deals in particular with Search engine indexing. His research in World Wide Web tackles topics such as Multimedia which are related to areas like The Internet. Many of his studies involve connections with topics such as Software engineering and Database.
Qing Li spends much of his time researching Artificial intelligence, Natural language processing, Machine learning, Representation and Pattern recognition. His Deep learning, Artificial neural network, Convolutional neural network, Embedding and Sentence study are his primary interests in Artificial intelligence. His Natural language processing research incorporates elements of Word and Task.
His biological study spans a wide range of topics, including Domain, Social media, Feature learning and Cluster analysis. Qing Li interconnects Adversarial system and Recommender system in the investigation of issues within Domain. His Pattern recognition research includes themes of Image and Modal.
His main research concerns Artificial intelligence, Natural language processing, Representation, Feature learning and Task. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Sequence. The various areas that Qing Li examines in his Feature learning study include Adversarial system, Recommender system, Human–computer interaction and Gradient descent.
His research integrates issues of Embedding and Set in his study of Task. As part of the same scientific family, Qing Li usually focuses on Convolutional neural network, concentrating on Hidden Markov model and intersecting with Data mining. The study incorporates disciplines such as Benchmark and Pattern recognition in addition to Contextual image classification.
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.
Least Squares Generative Adversarial Networks
Xudong Mao;Qing Li;Haoran Xie;Raymond Y.K. Lau.
international conference on computer vision (2017)
Unified Modeling Language
Qing Li;Yu-Liu Chen.
Algorithms for Materialized View Design in Data Warehousing Environment
Jian Yang;Kamalakar Karlapalem;Qing Li.
very large data bases (1997)
Exploiting Topic based Twitter Sentiment for Stock Prediction
Jianfeng Si;Arjun Mukherjee;Bing Liu;Qing Li.
meeting of the association for computational linguistics (2013)
A meta modelng approach to workflow management systems supporting exception handling
Dickson K. W. Chiu;Qing Li;Kamalakar Karlapalem.
Information Systems (1999)
Graph Neural Networks for Social Recommendation
Wenqi Fan;Yao Ma;Qing Li;Yuan He.
the web conference (2019)
Typicality-Based Collaborative Filtering Recommendation
Yi Cai;Ho-fung Leung;Qing Li;Huaqing Min.
IEEE Transactions on Knowledge and Data Engineering (2014)
FACTS: A Framework for Fault-Tolerant Composition of Transactional Web Services
An Liu;Qing Li;Liusheng Huang;Mingjun Xiao.
IEEE Transactions on Services Computing (2010)
Web interface-driven cooperative exception handling in ADOME workflow management system
D.K.W. Chiu;Qing Li;K. Karlapalem.
web information systems engineering (2000)
Workflow View Driven Cross-Organizational Interoperability in a Web Service Environment
Dickson K. W. Chiu;S. C. Cheung;Sven Till;Kamalakar Karlapalem.
Information Technology & Management (2004)
Profile was last updated on December 6th, 2021.
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