His main research concerns World Wide Web, Web service, Services computing, Web modeling and WS-Policy. His World Wide Web study combines topics in areas such as Software system, Orchestration and Data science. His Web service research includes themes of Provisioning, Information retrieval and Service.
His study looks at the intersection of Services computing and topics like Service delivery framework with Service system. His research in Web modeling intersects with topics in Web standards and Web development. His biological study deals with issues like WS-I Basic Profile, which deal with fields such as Business Process Execution Language, Web engineering and Integrated services.
His primary areas of investigation include World Wide Web, Web service, Artificial intelligence, Data mining and The Internet. His research ties Service and World Wide Web together. His is involved in several facets of Web service study, as is seen by his studies on WS-Policy, Web modeling, Service-oriented architecture and Data Web.
The various areas that Quan Z. Sheng examines in his WS-Policy study include WS-Addressing and WS-I Basic Profile. His studies in Artificial intelligence integrate themes in fields like Machine learning, Computer vision and Pattern recognition. His Data mining study frequently draws connections between related disciplines such as Information retrieval.
The scientist’s investigation covers issues in Artificial intelligence, Machine learning, Deep learning, Data science and Information retrieval. Quan Z. Sheng has researched Artificial intelligence in several fields, including Recommender system, Wearable computer and Natural language processing. His biological study spans a wide range of topics, including Heuristic and Identification.
Quan Z. Sheng works mostly in the field of Data science, limiting it down to topics relating to Key and, in certain cases, The Internet, as a part of the same area of interest. His research on The Internet concerns the broader World Wide Web. His Information retrieval research is multidisciplinary, incorporating elements of Mashup, Service and Cache.
His primary areas of study are Artificial intelligence, Information retrieval, Data science, Machine learning and Deep learning. His Artificial intelligence study integrates concerns from other disciplines, such as Big data, Wearable computer, Computer vision and Pattern recognition. His work deals with themes such as Social media, Focus, Data mining and Service, which intersect with Information retrieval.
Quan Z. Sheng interconnects Field, Key and Categorization in the investigation of issues within Data science. His Mashup study introduces a deeper knowledge of Web service. His study with Recommender system involves better knowledge in World Wide Web.
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.
Quality driven web services composition
Liangzhao Zeng;Boualem Benatallah;Marlon Dumas;Jayant Kalagnanam.
the web conference (2003)
The Self-Serv environment for Web services composition
B. Benatallah;Q.Z. Sheng;M. Dumas.
IEEE Internet Computing (2003)
Declarative composition and peer-to-peer provisioning of dynamic Web services
B. Benatallah;M. Dumas;Q.Z. Sheng;A.H.H. Ngu.
international conference on data engineering (2002)
IoT Middleware: A Survey on Issues and Enabling Technologies
Anne H. Ngu;Mario Gutierrez;Vangelis Metsis;Surya Nepal.
IEEE Internet of Things Journal (2017)
Web services composition: A decade's overview
Quan Z. Sheng;Xiaoqiang Qiao;Athanasios V. Vasilakos;Claudia Szabo.
Information Sciences (2014)
ContextUML: a UML-based modeling language for model-driven development of context-aware Web services
Q.Z. Sheng;B. Benatallah.
international conference on mobile business (2005)
SELF-SERV: a platform for rapid composition of web services in a peer-to-peer environment
Quan Z. Sheng;Boualem Benatallah;Marlon Dumas;Eileen Oi-Yan Mak.
very large data bases (2002)
Trust management of services in cloud environments: Obstacles and solutions
Talal H. Noor;Quan Z. Sheng;Sherali Zeadally;Jian Yu.
ACM Computing Surveys (2013)
When things matter
Yongrui Qin;Quan Z. Sheng;Nickolas J.G. Falkner;Schahram Dustdar.
Journal of Network and Computer Applications (2016)
Trust as a service: a framework for trust management in cloud environments
Talal H. Noor;Quan Z. Sheng.
web information systems engineering (2011)
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